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        "#   Introduction to Hamiltonian Neural Network\n",
        "\n",
        "by [Abhay Shinde](https://github.com/a-b-h-a-y-s-h-i-n-d-e), [José A. Sigüenza](https://github.com/JoseAntonioSiguenza)\n",
        "\n",
        "In this tutorial, we will be using Hamiltoninan Neural Networks(HNN) to model the dynamics of a simple mass-spring system. The goal is to show how HNNs can learn the underlying physics of a system rather than just fitting data like a typical neural network.\n",
        "\n",
        "This approach preserves the structure of physical laws and significantly reduces error accumulation over time, which is common in standard neural networks during long-term simulations. HNNs are especially useful in systems where conservation of energy is important, such as mechanical oscillators, planetary motion, and other classical systems.\n",
        "\n",
        "We will use some tools of Deepchem ( like TorchModel, NumpyDataset, MultilayerPerceptron) and additional packages to create a HNN model that learns total energy (Hamiltonian) of the system and simulates its dynamics using Hamilton's equations.\n",
        "\n",
        "## Colab\n",
        "This tutorial and the rest in this sequence are designed to be done in Google colab. If you'd like to open this notebook in colab, you can use the following link.\n",
        "\n",
        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/deepchem/deepchem/blob/master/examples/tutorials/Introduction_to_Hamiltonian_Neural_Network.ipynb)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8Kjx37zT-DTX"
      },
      "source": [
        "# Introduction to Hamiltonian mechanics\n",
        "In classical mechanics, we often describe a physical system using phase space coordinates, which are just:\n",
        "\n",
        "* `q`: position\n",
        "* `p`: momentum  \n",
        "\n",
        "Together, they define the state of the system at any time.\n",
        "Now, instead of working with forces (like in Newton's laws), Hamiltonian mechanics gives us a different approach. It describes how `q` and `p` evolve over time using something called the Hamiltonian — usually representing the total energy of the system (kinetic + potential).\n",
        "The dynamics are given by these equations:\n",
        "\n",
        "$$\n",
        "\\frac{dq}{dt} = \\frac{\\partial H}{\\partial p}, \\quad \\frac{dp}{dt} = -\\frac{\\partial H}{\\partial q}\n",
        "$$\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jlY5G0bX-3fA"
      },
      "source": [
        "# HNN vs Traditional Neural Networks\n",
        "\n",
        "\n",
        "\n",
        "<p align=\"center\">\n",
        "  <img src=\"https://greydanus.github.io/assets/hamiltonian-nns/overall-idea.png\" width=\"800\"/>\n",
        "</p>\n",
        "\n",
        "<p align=\"center\">\n",
        "  <em>Figure: Overall idea of Hamiltonian Neural Networks. Source: <a href=\"#Bibliography\">[4]</a></em>\n",
        "</p>\n",
        "\n",
        "Neural networks are good at fitting data, but they often ignore the underlying physics of the system. Hamiltonian Neural Networks (HNNs) take a different approach — instead of predicting the next state directly, they learn the system's Hamiltonian and use it to generate dynamics.\n",
        "\n",
        "\n",
        "HNNs work by learning a scalar-valued function H(q, p), which represents the total energy (Hamiltonian) of the system. Once trained, the network outputs this Hamiltonian, and we use Hamilton's equations to compute how position and momentum evolve over time.\n",
        "\n",
        "To get these dynamics, we use a structure called the **symplectic gradient**. For H(q, p), the time derivatives of position and momentum are computed using:\n",
        "$$\n",
        "\\frac{d}{dt}\n",
        "\\begin{bmatrix}\n",
        "q \\\\\n",
        "p\n",
        "\\end{bmatrix}\n",
        "=\n",
        "\\begin{bmatrix}\n",
        "\\frac{\\partial H}{\\partial p} \\\\\n",
        "- \\frac{\\partial H}{\\partial q}\n",
        "\\end{bmatrix}\n",
        "$$\n",
        "\n",
        "\n",
        "This operation is often written using a symplectic matrix **J**:\n",
        "$$\n",
        "\\frac{dz}{dt} = J \\nabla_z H(z)\n",
        "\\quad \\text{where} \\quad\n",
        "z =\n",
        "\\begin{bmatrix}\n",
        "q \\\\\n",
        "p\n",
        "\\end{bmatrix},\n",
        "\\quad\n",
        "J =\n",
        "\\begin{bmatrix}\n",
        "0 & 1 \\\\\n",
        "-1 & 0\n",
        "\\end{bmatrix}\n",
        "$$\n",
        "\n",
        "### The role of symplectic gradient\n",
        "\n",
        "The symplectic gradient helps us get the correct time evolution of the system using the Hamiltonian. Instead of predicting future states directly, we use the gradient of the Hamiltonian with a fixed matrix (called the symplectic matrix) to get how position and momentum change over time. This method keeps the system's physical behavior realistic, like conserving energy."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "va7_dNWZDnQz"
      },
      "source": [
        "# The mass-spring experiment\n",
        "\n",
        "We are simulating HNN on a experiment such as mass-spring system\n",
        "\n",
        "<p align=\"center\">\n",
        "  <img src=\"https://i.ytimg.com/vi/lZPtFDXYQRU/maxresdefault.jpg\" width=\"800\"/>\n",
        "</p>\n",
        "<p align=\"center\">\n",
        "  <em>Figure: Mass-spring system illustration. Source: <a href=\"#Bibliography\">[5]</a></em>\n",
        "</p>\n",
        "\n",
        "In simple terms, the object is attached to a spring, we denote co-ordinates of object on basis of its position `q` and its momentum `p`, Initially both the (q, p) values are zero, so we slightly push the object to simulate the experiment.\n",
        "\n",
        "The equation is stated as :\n",
        "$$\n",
        "\\mathcal{H} = \\frac{1}{2} k q^2 + \\frac{p^2}{2m}\n",
        "$$\n",
        "\n",
        "\n",
        "- The term $\\frac{p^2}{2m}$ represents the **kinetic energy** of the system.  \n",
        "- The term $\\frac{1}{2} k q^2$ represents the **potential energy** stored in the spring.  \n",
        "- The total energy, represented by the Hamiltonian $H$, remains **constant** throughout the motion.\n",
        "\n",
        "Now, lets start with the dataset for mass-spring experiment.\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NUdrZkjPHhCh"
      },
      "source": [
        "# Explanation of Dataset script\n",
        "\n",
        "The author of HNN paper has also provided scritps to generate synthetic dataset for each of the experiments, so we are here using it, the explanation is as follows:\n",
        "\n",
        "### 1. hamiltonian_fn\n",
        "* This methods defines/implements the main equation of hamiltonian mechanics for mass-spring experiment.\n",
        "* Here, the mass `m` is assumed as 1/2 and spring constant `k` is assumed as 2 that's why the final equation is:\n",
        "$$\n",
        "H(q, p) = q^2 + p^2\n",
        "$$\n",
        "\n",
        "### 2. dynamics_fn\n",
        "* This computes the time derivative of coordinates `(q, p)` using the `hamiltonian_fn` to get \"ground truth\".\n",
        "* Also constructs the symplectic gradient (S) by calculating `dqdt` and `dpdt` :\n",
        "$$\n",
        "\\frac{dq}{dt} = \\frac{\\partial H}{\\partial p}, \\quad \\frac{dp}{dt} = -\\frac{\\partial H}{\\partial q}\n",
        "$$\n",
        "\n",
        "\n",
        "### 3. get_trajectory\n",
        "\n",
        "* Simulates the true dynamics of the system using numerical integration.\n",
        "\n",
        "### 4. get_dataset\n",
        "\n",
        "*  Generates a full dataset by calling `get_trajectory` multiple times.\n",
        "* it contains `x` : state vectors and `dx` : their derivatives\n",
        "\n",
        "\n",
        "### 5. get_field\n",
        "* Creates a grid in phase space (q vs p)\n",
        "* Computes `dynamics_fn` for each grid point\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "nDK8xI9O_qAY"
      },
      "outputs": [],
      "source": [
        "# Hamiltonian Neural Networks | 2019\n",
        "# Sam Greydanus, Misko Dzamba, Jason Yosinski\n",
        "\n",
        "import autograd\n",
        "import autograd.numpy as np\n",
        "\n",
        "import scipy.integrate\n",
        "solve_ivp = scipy.integrate.solve_ivp\n",
        "\n",
        "def hamiltonian_fn(coords):\n",
        "    q, p = np.split(coords,2)\n",
        "    H = p**2 + q**2 # spring hamiltonian (linear oscillator)\n",
        "    return H\n",
        "\n",
        "def dynamics_fn(t, coords):\n",
        "    dcoords = autograd.grad(hamiltonian_fn)(coords)\n",
        "    dqdt, dpdt = np.split(dcoords,2)\n",
        "    S = np.concatenate([dpdt, -dqdt], axis=-1)\n",
        "    return S\n",
        "\n",
        "def get_trajectory(t_span=[0,3], timescale=10, radius=None, y0=None, noise_std=0.1, **kwargs):\n",
        "    t_eval = np.linspace(t_span[0], t_span[1], int(timescale*(t_span[1]-t_span[0])))\n",
        "\n",
        "    # get initial state\n",
        "    if y0 is None:\n",
        "        y0 = np.random.rand(2)*2-1\n",
        "    if radius is None:\n",
        "        radius = np.random.rand()*0.9 + 0.1 # sample a range of radii\n",
        "    y0 = y0 / np.sqrt((y0**2).sum()) * radius ## set the appropriate radius\n",
        "\n",
        "    spring_ivp = solve_ivp(fun=dynamics_fn, t_span=t_span, y0=y0, t_eval=t_eval, rtol=1e-10, **kwargs)\n",
        "    q, p = spring_ivp['y'][0], spring_ivp['y'][1]\n",
        "    dydt = [dynamics_fn(None, y) for y in spring_ivp['y'].T]\n",
        "    dydt = np.stack(dydt).T\n",
        "    dqdt, dpdt = np.split(dydt,2)\n",
        "\n",
        "    # add noise\n",
        "    q += np.random.randn(*q.shape)*noise_std\n",
        "    p += np.random.randn(*p.shape)*noise_std\n",
        "    return q, p, dqdt, dpdt, t_eval\n",
        "\n",
        "def get_dataset(seed=0, samples=50, test_split=0.5, **kwargs):\n",
        "    data = {'meta': locals()}\n",
        "\n",
        "    # randomly sample inputs\n",
        "    np.random.seed(seed)\n",
        "    xs, dxs = [], []\n",
        "    for s in range(samples):\n",
        "        x, y, dx, dy, t = get_trajectory(**kwargs)\n",
        "        xs.append( np.stack( [x, y]).T )\n",
        "        dxs.append( np.stack( [dx, dy]).T )\n",
        "\n",
        "    data['x'] = np.concatenate(xs)\n",
        "    data['dx'] = np.concatenate(dxs).squeeze()\n",
        "\n",
        "    # make a train/test split\n",
        "    split_ix = int(len(data['x']) * test_split)\n",
        "    split_data = {}\n",
        "    for k in ['x', 'dx']:\n",
        "        split_data[k], split_data['test_' + k] = data[k][:split_ix], data[k][split_ix:]\n",
        "    data = split_data\n",
        "    return data\n",
        "\n",
        "def get_field(xmin=-1.2, xmax=1.2, ymin=-1.2, ymax=1.2, gridsize=20):\n",
        "    field = {'meta': locals()}\n",
        "\n",
        "    # meshgrid to get vector field\n",
        "    b, a = np.meshgrid(np.linspace(xmin, xmax, gridsize), np.linspace(ymin, ymax, gridsize))\n",
        "    ys = np.stack([b.flatten(), a.flatten()])\n",
        "\n",
        "    # get vector directions\n",
        "    dydt = [dynamics_fn(None, y) for y in ys.T]\n",
        "    dydt = np.stack(dydt).T\n",
        "\n",
        "    field['x'] = ys.T\n",
        "    field['dx'] = dydt.T\n",
        "    return field"
      ]
    },
    {
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      "execution_count": 2,
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",
            "text/plain": [
              "<Figure size 450x450 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "field = get_field(gridsize=15)\n",
        "data = get_dataset()\n",
        "\n",
        "# plot config\n",
        "fig = plt.figure(figsize=(3, 3), facecolor='white', dpi=150)\n",
        "\n",
        "x, y, dx, dy, t = get_trajectory(radius=0.7, y0=np.array([1, 0]))\n",
        "plt.scatter(x, y, c=t, s=14, label='trajectory')\n",
        "plt.quiver(field['x'][:, 0], field['x'][:, 1], field['dx'][:, 0], field['dx'][:, 1],\n",
        "           cmap='gray_r', color=(.5, .5, .5))\n",
        "\n",
        "plt.xlabel(\"$x$\", fontsize=14)\n",
        "plt.ylabel(r\"$\\frac{dx}{dt}$\", rotation=0, fontsize=14)\n",
        "plt.title(\"Dynamics of the Mass-Spring System\")\n",
        "plt.legend(loc='upper right')\n",
        "plt.tight_layout()\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "T9nCyppMjhKK"
      },
      "source": [
        "Now lets load the HNN model and fit our dataset and fit on our dataset"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OOHMt9gyHhCk"
      },
      "source": [
        "## Setup"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 658
        },
        "id": "AablVRomj_Hn",
        "outputId": "24e25e7e-313d-4a39-e9b5-b87bce7ae554"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: deepchem in /usr/local/lib/python3.11/dist-packages (2.8.1.dev20250722090935)\n",
            "Requirement already satisfied: joblib in /usr/local/lib/python3.11/dist-packages (from deepchem) (1.5.1)\n",
            "Requirement already satisfied: numpy<2 in /usr/local/lib/python3.11/dist-packages (from deepchem) (1.26.4)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.11/dist-packages (from deepchem) (2.2.2)\n",
            "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.11/dist-packages (from deepchem) (1.6.1)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.11/dist-packages (from deepchem) (1.13.1)\n",
            "Requirement already satisfied: scipy>=1.10.1 in /usr/local/lib/python3.11/dist-packages (from deepchem) (1.16.0)\n",
            "Requirement already satisfied: rdkit in /usr/local/lib/python3.11/dist-packages (from deepchem) (2025.3.3)\n",
            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.11/dist-packages (from pandas->deepchem) (2.9.0.post0)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.11/dist-packages (from pandas->deepchem) (2025.2)\n",
            "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.11/dist-packages (from pandas->deepchem) (2025.2)\n",
            "Requirement already satisfied: Pillow in /usr/local/lib/python3.11/dist-packages (from rdkit->deepchem) (11.3.0)\n",
            "Requirement already satisfied: threadpoolctl>=3.1.0 in /usr/local/lib/python3.11/dist-packages (from scikit-learn->deepchem) (3.6.0)\n",
            "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from sympy->deepchem) (1.3.0)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.11/dist-packages (from python-dateutil>=2.8.2->pandas->deepchem) (1.17.0)\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "WARNING:deepchem.feat.molecule_featurizers.rdkit_descriptors:No normalization for SPS. Feature removed!\n",
            "WARNING:deepchem.feat.molecule_featurizers.rdkit_descriptors:No normalization for AvgIpc. Feature removed!\n",
            "WARNING:deepchem.feat.molecule_featurizers.rdkit_descriptors:No normalization for NumAmideBonds. Feature removed!\n",
            "WARNING:deepchem.feat.molecule_featurizers.rdkit_descriptors:No normalization for NumAtomStereoCenters. Feature removed!\n",
            "WARNING:deepchem.feat.molecule_featurizers.rdkit_descriptors:No normalization for NumBridgeheadAtoms. Feature removed!\n",
            "WARNING:deepchem.feat.molecule_featurizers.rdkit_descriptors:No normalization for NumHeterocycles. Feature removed!\n",
            "WARNING:deepchem.feat.molecule_featurizers.rdkit_descriptors:No normalization for NumSpiroAtoms. Feature removed!\n",
            "WARNING:deepchem.feat.molecule_featurizers.rdkit_descriptors:No normalization for NumUnspecifiedAtomStereoCenters. Feature removed!\n",
            "WARNING:deepchem.feat.molecule_featurizers.rdkit_descriptors:No normalization for Phi. Feature removed!\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m W&B installed but not logged in.  Run `wandb login` or set the WANDB_API_KEY env variable.\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.11/dist-packages/tensorflow/python/util/deprecation.py:588: calling function (from tensorflow.python.eager.polymorphic_function.polymorphic_function) with experimental_relax_shapes is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "experimental_relax_shapes is deprecated, use reduce_retracing instead\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m W&B installed but not logged in.  Run `wandb login` or set the WANDB_API_KEY env variable.\n",
            "WARNING:deepchem.models.torch_models:Skipped loading modules with pytorch-geometric dependency, missing a dependency. No module named 'torch_geometric'\n",
            "WARNING:deepchem.models:Skipped loading modules with pytorch-geometric dependency, missing a dependency. cannot import name 'DMPNN' from 'deepchem.models.torch_models' (/usr/local/lib/python3.11/dist-packages/deepchem/models/torch_models/__init__.py)\n",
            "WARNING:deepchem.models:Skipped loading modules with pytorch-lightning dependency, missing a dependency. No module named 'lightning'\n",
            "WARNING:deepchem.models:Skipped loading some Jax models, missing a dependency. No module named 'haiku'\n"
          ]
        },
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'2.8.1.dev'"
            ]
          },
          "execution_count": 3,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "!pip install --pre deepchem\n",
        "import deepchem\n",
        "deepchem.__version__"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H7gOERPvkWEI",
        "outputId": "31de589f-7b95-4edd-d0c4-4cbacd2b1990"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0.04193680286407471"
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "from deepchem.data import NumpyDataset\n",
        "from deepchem.models.torch_models.hnn import HNN, HNNModel\n",
        "\n",
        "# loading dataset in NumpyDataset\n",
        "train_dataset = NumpyDataset(X=data['x'], y=data['dx'])\n",
        "test_dataset = NumpyDataset(X=data['test_x'], y=data['test_dx'])\n",
        "\n",
        "# creating model instance\n",
        "model = HNNModel(batch_size=64)\n",
        "\n",
        "# training for 100 epochs\n",
        "model.fit(train_dataset, nb_epoch=100)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FF9Yw4ANlvzR",
        "outputId": "8f4f9bb8-8ace-44f8-8401-28967143b116"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[[-0.3033807   1.46951042]]\n",
            "[[-0.27135593  1.7031634 ]]\n"
          ]
        }
      ],
      "source": [
        "H_pred = model.predict(test_dataset)\n",
        "# output.shape = (n_sample, 2)\n",
        "\n",
        "print(test_dataset.y[:1])\n",
        "print(H_pred[:1])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 564
        },
        "id": "2t0w3UtZIM-z",
        "outputId": "c3b97a7b-c353-416d-cd8b-a9ea4692d017"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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D4Pjx47WsORe+fL/77rt6t72a83Spr7+LHejOcylLlSzLTZahKdTX5sa25XJcTTtnzpzJf/7zH3Jzc7G1teW3337jlltuqRXFMWPGDAYNGsSyZctYt24db7zxBq+99hq//vor48aNa7S8jeHZZ5/l22+/5bXXXmtQ+H1QUBC33347n376aaPDYtVqdc39eznqu55t7RltCRpi+XVzc+Pw4cOsXbuWNWvWsGbNGr766itmzZpVr7N0e0coIx2Y2267jf/7v//j6NGjLF68mE6dOtGrV6+a5cHBwZSWll7xpREcHMzatWvJz8+/rHWkvk7B1dUVKysr4uLi6iw7deoUKpUKX1/fRrTq6mhomy/G1dUVS0tL4uPj6yyrr20NZdy4cajVar7//vurDrc+P5RzqXPt4uJSEybt6OhYr+PnxV9wDaWlzk9DOG8VuLg99bWlJTPBzpw5kxdeeIGlS5fi7u5OcXExN998c531PD09WbBgAQsWLCA7O5sePXrwn//8p8WVkeDgYG6//XY++eSTOk7jl+K5557ju+++q3GgvBY09Bn19/dn48aNlJaW1rKONOR+Cw4Oxmw2c/LkSaKjoy+5XkPvlwufvQstYefn1TfM2hB0Oh0TJ05k4sSJmM1mFixYwCeffML//d//ERIS0qR9tlXEME0H5nzn9vzzz3P48OE6nd2MGTPYtWsXa9eurbNtYWEhRqMRUHwTZFnmhRdeqLPehV+M1tbWdToEtVrN6NGjWbFiRS3/laysLBYvXszAgQOxs7NrahMbTUPbfDFqtZoxY8awfPlyUlJSaubHxsbWu6+Ghvb6+flx5513smbNGt5///1612mo9cHT05Po6Gi+/vrrWtfh+PHjrFu3rlZiuODgYIqKijh69GjNvIyMjDpj+g2lseenOfH390etVtfx9/nwww/rrHteGWtoBE5jCA8Pp2vXrvz000/89NNPeHp6Mnjw4JrlJpOJoqKiWtu4ubnh5eV1zTKTPvfccxgMBl5//fUGrX+hApOZmdnC0ik09BkdP348RqORjz76qGa5yWRqULK2KVOmoFKpePHFF+uEC1/pnVYfPXv2xM3NjY8//rjWtVyzZg2xsbFMmDDhivu4mIszZKtUqhrfoPaWybYhCMtIByYwMJD+/fuzYsUKgDrKyD/+8Q9+++03brjhBubMmUNMTAxlZWUcO3aMJUuWkJycjIuLC8OGDeOOO+7g3XffJT4+nrFjx2I2m9m2bRvDhg2rCR+OiYlhw4YNNUmNAgMD6dOnD//+979Zv349AwcOZMGCBWg0Gj755BOqqqoa/FJsLhra5vp44YUX+OOPPxg0aBALFizAaDTy3nvvERERUatTh4aH9gK8/fbbJCUl8eCDD/Ljjz8yceJE3NzcyM3NZceOHaxcubLBfhdvvPEG48aNo1+/fsybN68mtNfe3r5W1tGbb76Zf/7zn0ydOpWHHnqI8vJyPvroIzp37tzknBeNOT/Nib29PTfddBPvvfcekiQRHBzM77//Xq//T0xMDAAPPfQQY8aMqXH2bi5mzpzJ888/j16vZ968ebWcI0tKSvDx8eHGG28kKioKGxsbNmzYwL59+3jrrbeaTYbLcV65aIyZ//zwTlxcHBERES0onUJDn9GJEycyYMAAnnrqKZKTk+nSpQu//vprHYWvPkJCQnj22Wd56aWXGDRoENOmTcPCwoJ9+/bh5eXFK6+8Aij3y0cffcS///1vQkJCcHNzq2P5ANBqtbz22mvMnTuXIUOGcMstt9SE9gYEBPDoo482+jzMnz+f/Px8hg8fjo+PD2fPnuW9994jOjqa8PDwRu+vzdN6gTyCa8EHH3wgA3Lv3r3rXV5SUiI//fTTckhIiKzT6WQXFxe5f//+8ptvvilXV1fXrGc0GuU33nhDDgsLk3U6nezq6iqPGzdOPnDgQM06p06dkgcPHixbWlrKQK2Q2oMHD8pjxoyRbWxsZCsrK3nYsGHyzp07a8lyYWhhQzgfjvnGG29ccp2LQ3sb02YuCu2VZVnesmWLHBMTI+t0OjkoKEj++OOP6w2HbWho73mMRqP81VdfycOHD5ednJxkjUYju7i4yCNGjJA//vjjWuGCV2r3hg0b5AEDBsiWlpaynZ2dPHHiRPnkyZN11lu3bp0cGRkp63Q6OTQ0VP7uu+8uGdpbXzhqfee2oefnSlwqtPdSYbE5OTny9OnTZSsrK9nR0VG+55575OPHj9cJ8TQajfKDDz4ou7q6ypIk1ch1uXNa331wKeLj42tCbbdv315rWVVVlfyPf/xDjoqKkm1tbWVra2s5KipK/vDDD6+43ys9G/WF3V4Y2nuxjOfDrS8V2nsx58NRGxPaeyUuJZ8sN/wZzcvLk++44w7Zzs5Otre3l++44w750KFDVwztPc+XX34pd+/eXbawsJAdHR3lIUOGyOvXr69ZnpmZKU+YMEG2tbWVgZp78lLh5D/99FPN/pycnOTbbrtNTktLa9D5uVjGJUuWyKNHj5bd3NxknU4n+/n5yffcc4+ckZFxyXPanpFk+Rp7oAkEAoFAIBBcgPAZEQgEAoFA0KoIZUQgEAgEAkGrIpQRgUAgEAgErYpQRgQCgUAgELQqQhkRCAQCgUDQqghlRCAQCAQCQasikp5dAbPZTHp6Ora2ti2aSlogEAgEgo6GLMuUlJTg5eVVp0LyhQhl5Aqkp6df09opAoFAIBB0NFJTU/Hx8bnkcqGMXIHzJd5TU1OvaQ2V+jAYDKxbt47Ro0ej1WpbVZbrFXENWhdx/lsfcQ1an/Z0DYqLi/H19a3pSy+FUEauwPmhGTs7uzahjFhZWWFnZ9fmb8COirgGrYs4/62PuAatT3u8BldycxAOrAKBQCAQCFoVoYwIBAKBQCBoVYQyIhAIBAKBoFURPiMCgUAgqIMsyxiNRkwmU635BoMBjUZDZWVlnWWCa0NbugZqtRqNRnPVqS+EMiIQCASCWlRXV5ORkUF5eXmdZbIs4+HhQWpqqsi91Eq0tWtgZWWFp6cnOp2uyfsQyohAIBAIajCbzSQlJaFWq/Hy8kKn09Xq8MxmM6WlpdjY2Fw2iZWg5Wgr10CWZaqrq8nJySEpKYlOnTo1WR6hjAgEAoGghurqasxmM76+vlhZWdVZbjabqa6uRq/XC2WklWhL18DS0hKtVsvZs2drZGoK4k4SCAQCQR1au5MTtB+a414Rd5tAIBAIBIJWRSgjAoFAIBAIWhXhMyIQCASCBrFwIciyRFWVHgsLiZYO5Fi4sGX335ZYuHAhy5cv5/Dhw60tCkOHDiU6Opq33377mh1TWEYEAoFA0GHIzMzk4YcfJiQkBL1ej7u7OwMGDOCjjz6qN1S5PbBw4UIkSaqZ1Go1jo6OqNXqmnlNYfPmzUiSRGFhYfMK3ASEZUQgEAgEHYLExEQGDBiAg4MDL7/8Ml27dsXCwoJjx47x6aef4u3tzaRJk+rd1mAwtNmic0888QT33ntvze9evXoxa9Ys7r///nqdR6urq68q50drICwjAoFAIOgQLFiwAI1Gw/79+5kxYwbh4eEEBQUxefJkVq1axcSJE2vWlSSJjz76iEmTJmFtbc1//vMfAD766COCg4PR6XSEhoby7bff1myTnJyMJEm1hlIKCwuRJInNmzcDf1sbNm7cSM+ePbGysqJ///7ExcXVkvXVV1/F3d0dW1tb5s2bR2Vl5SXbZWNjg4eHR82kVqtrzbv55pt54IEHeOSRR3BxcWHMmDFXlDU5OZlhw4YB4OjoiCRJzJkzp2Zds9nMk08+iZOTEx4eHixs4TEzoYwIBAKBoN2Tl5fHunXruP/++7G2tq53nYuHMxYuXMjUqVM5duwYd955J8uWLePhhx/m8ccf5/jx49xzzz3MnTuXTZs2NVqeZ599lrfeeov9+/ej0Wi48847a5b9/PPPLFy4kJdffpn9+/fj6enJhx9+2OhjXMjXX3+NTqdjx44dfPzxx1dc39fXl6VLlwIQFxdHRkYG77zzTq39WVtbs2fPHl5//XVefPFF1q9ff1UyXg4xTCMQCASCdk9CQgKyLBMaGlprvouLS43V4f777+e1116rWXbrrbcyd+7cmt+33HILc+bMYcGCBQA89thj7N69mzfffLPGitBQ/vOf/zBkyBAAnnrqKSZMmEBlZSV6vZ63336befPmMW/ePAD+/e9/s2HDhstaR65Ep06deP3112t+JycnX3Z9tVqNk5MTAG5ubjg4ONRa3q1bN/71r3/V7Pv9999n48aNjBo1qskyXg5hGREIBILzpKSA0UhhIXz3HezZAwUFrS2U4GrYu3cvhw8fJiIigqqqqlrLevbsWet3bGwsAwYMqDVvwIABxMbGNvq43bp1q/nf09MTgOzs7Jrj9OnTp9b6/fr1a/QxLiQmJuaqtr+YC+UHpQ3n5W8JhGVEIBBcV2y+4wuMaDBq9Bi1lrX+OmTHYVuYRo5HV3Lso0mI92LNGglXV+jZE3r1ApGYtG0SEhKCJEl1fDOCgoIAJW35xVxqOOdSnHcWlWW5Zp7BYKh33QudYc8PD5nN5kYdrzFc3JbGyFofFzvzSpLUovKLx0ogEFxXBN0xgM43diNyvB89BtvQJ8bIoNBshvvE0csvi4jgSgbp9xFz6HP6Zy1jZJ8Spk+H3r2FItKWcXZ2ZtSoUbz//vuUlZU1aR/h4eHs2LGj1rwdO3bQpUsXAFxdXQHIyMioWd6UvCDh4eHs2bOn1rzdu3c3ej+XoyGyno+4MZlMzXrspiAsIwKB4LrCb3RY/QvMZli9GmxtKXfxI9rdGzuX9hUeeb3z4YcfMmDAAHr27MnChQvp1q0bKpWKffv2cerUqSsOZfzjH/9gxowZdO/enZEjR7Jy5Up+/fVXNmzYACjWlb59+/Lqq68SGBhIdnY2zz33XKPlfPjhh5kzZw49e/ZkwIABfP/995w4caLGitMcNERWf39/JEni999/Z/z48VhaWmJjY9NsMjQGoYwIBAIBKGaPG24AoG6tWgEoGVHNZpni4krs7HSoVC2cgrWRBAcHc+jQIV5++WWefvpp0tLSsLCwoEuXLjzxxBM1jqmXYsqUKbzzzju8+eabPPzwwwQGBvLVV18xdOjQmnW+/PJL5s2bR0xMDKGhobz++uuMHj26UXLOnDmTM2fO8OSTT1JZWcn06dO57777WLt2bVOafUmuJKu3tzcvvPACTz31FHPnzmXWrFksWrSoWWVoKJJ84YCSoA7FxcXY29tTVFSEnZ1dq8piMBhYvXo148ePb7PJeTo64hq0LuL8tzyVlZUkJSURGBhYbzl4s9lMcXExdnZ2orJvK9HWrsHl7pmG9qGt3wqBQCAQCATXNUIZEQgEAoFA0KoIZUQgEAgEAkGrIpQRgUAgEAgErYpQRgQCgUAgELQqQhkRCAQCgUDQqghlRCAQCAQCQasilBGBQCAQCAStilBGBAKBQCAQtCoiHbxAIBAIGsbChUiyjL6qCsnCAqQWTge/cGHL7r+JzJkzh8LCQpYvXw7A0KFDiY6O5u23376mcmzevJkRI0ZQUFCAg4PDNT12cyMsIwKBQCDoEMyZMwdJkpAkCZ1OR0hICC+++CJGo7FFj/vrr7/y0ksvNWjdzZs3I0kShYWFLSpTe0NYRgQCgUDQYRg7dixfffUVVVVVrF69mvvvvx+tVsvTTz9da73q6mp0uuapyuzk5NQs+7meEZYRgUAgEHQYLCws8PDwwN/fn/vuu4+RI0fy22+/MWfOHKZMmcJ//vMfvLy8CA0NBSA1NZUZM2bg4OCAk5MTkydPJjk5uWZ/JpOJxx57DAcHB5ydnXnyySe5uL7s0KFDeeSRR2p+V1VV8c9//hNfX18sLCwICQnhiy++IDk5mWHDhgHg6OiIJEnMmTMHUIrfvfLKKwQGBmJpaUlUVBRLliypdZzVq1fTuXNnrK2tmThxYi052ztCGREIBIKGIoqctzssLS2prq4GYOPGjcTFxbF+/Xp+//13DAYDY8aMwdbWlm3btrFjxw5sbGwYO3ZszTZvvfUWixYt4ssvv2T79u3k5+ezbNmyyx5z1qxZ/PDDD7z77rvExsbyySefYGNjg6+vL0uXLgUgLi6OjIwM3nnnHQBeeeUVvvnmGz7++GNOnDjBo48+yu23386WLVsARWmaNm0aEydO5ODBg9xxxx0888wzLXXarjlimEYgEAiAk1/tofzgKey8bXHwtcXJ3xaNgw2ylTVxS47h0MULl7JkNGpg8GBwc/t744oKKCwET8/WEl9wEbIss3HjRtauXcuDDz5ITk4O1tbWfP755zXDM9999x1ms5nPP/8c6S9n3K+++goHBwc2b97M6NGjefvtt3n66aeZNm0aAB9//DFr16695HFPnz7Nzz//zPr16xk5ciQAQUFBNcvPD+m4ubnVOJ1WVVXx8ssvs2HDBvr161ezzfbt2/nkk08YMmQIH330EcHBwbz11luYzWY8PT05c+YMr7/+evOeuFZCKCMCgUAAOEQHUFatJTm1lOINJUilybhYlOBAIeqjBymoLKfUXIVUVYmV7YdYd/JG37sruqgu4OwMGzdi9vaF/v1RdQ5p+UgTQb38/vvv2NjYYDAYMJvN3HrrrSxcuJD777+frl271vITOXLkCAkJCdja2tbaR2VlJWfOnKGoqIiMjAz69OlTs0yj0dCzZ886QzXnOXz4MGq1miFDhjRY5oSEBMrLyxk1alSt+dXV1XTv3h2A2NjYWnIA9O3bt8HHaOsIZUQgENSlvBwOHiQlU4tJ0mJho0Vvo0EfFoClk2WH7Ge9urvj1d0dUEZjCgshPV2ZzqXJ5Jwtx+/AMqxzz5JdZYcx2xqrHRY4JVXjYZ+IV5kR+5IkTi1Pwqe7K643DoGICKGUXGOGDRvGRx99hE6nw8vLC43m727O2tq61rqlpaXExMTw/fff19mPq6trk45vaWnZ6G1KS0sBWLVqFd7e3rWWWVhYNEmO9oZQRgQCQW0qKzEnp1C2+QBVsQWcOweVegfiO41HF2nJmDEQENDaQrYskgSOjsoUEQEgIZutyIy7gUXL7Kmq/lvBCAgAa8Npjh61Iy3fhVJ/V8orXfA7Ys9oDwkXl9ZqxfWJtbU1ISEhDVq3R48e/PTTT7i5uWFnZ1fvOp6enuzZs4fBgwcDYDQaOXDgAD169Kh3/a5du2I2m9myZUvNMM2FnLfMmEymmnldunTBwsKClJSUS1pUwsPD+e2332rN27Nnz5Ub2U4QyohAcL1jMFByIoX8A0mUH0+kMimDbJMz1Tp7vM3FpAQOpDByIMNGa4mMvH4/9CWVhI2PA7Nmg7W1Mmm155d2Bjqzfz+sWgV6PeTkwvLlMGgQ/BW4IWhj3HbbbbzxxhtMnjyZF198ER8fH86ePcuvv/7Kk08+iY+PDw8//DCvvvoqnTp1IiwsjP/+97+XzRESEBDA7NmzufPOO3n33XeJiori7NmzZGdnM2PGDPz9/ZEkid9//53x48djaWmJra0tTzzxBI8++ihms5mBAwdSVFTEjh07sLOzY/bs2dx777289dZb/OMf/+DOO+9k+/btfP3119fuZLUwQhkRCK5DZJOZYx9uo+JkEsbkVErN1pgDgtCH98FhSiBRoXa4lSVRqbOjKs2ZXr2gxtp99ChUVpJToictV4+VowVWnnbY+jpiawtqdas2rUWxtVWmS9GtG8TEdGCFbeFCZLOZyuJidHZ2SKr2HZBpZWXF1q1b+ec//8m0adMoKSnB29ubESNG1FhKHn/8cTIyMpg9ezYqlYo777yTqVOnUlRUdMn9fvTRRzzzzDMsWLCAvLw8/Pz8aiJfvL29eeGFF3jqqaeYO3cus2bNYtGiRbz00ku4urryyiuvkJiYiIODAz169KjZzs/Pj6VLl/Loo4/y3nvv0aNHD/79738zf/78lj9R1wBJvpQXjgCA4uJi7O3tKSoquqQZ71phMBhYvXo148ePR/v3J5ngGtKRrsHu51eh93PHsUcgHl2csNBfoQc1GuHcOap2HaR81xFKSiApCTLco0kMHIHO2ZYhQ5TOuKX6qI50/tsqlZWVJCUlERgYiF6vr7PcbDZTXFyMnZ0dqnaujLRX2to1uNw909A+tF1ZRrZu3cobb7zBgQMHyMjIYNmyZUyZMuWy22zevJnHHnuMEydO4Ovry3PPPVeTZEYguJ7p++KEyy6XyysoPpFK0dGzlJ9KoTo5ncJKPVkWfviUSqj8fDg9ZCwFVt4MHQi9el04bCEQCAQNp10pI2VlZURFRXHnnXfWxHxfjqSkJCZMmMC9997L999/z8aNG5k/fz6enp6MGTPmGkgsELQvzAYTB/+zBsOZFIwZOZTqnMDPD4tOPbAdMQXfzk70sq/AMr0LREaiOSgRGQlt0uE/Lo4qWYc22A+VtgOPHQkEHYB2pYyMGzeOcePGNXj9jz/+mMDAQN566y1A8Ubevn07//vf/4QyIhDUg0qrRrK1wX7KMJyi/XDxt0ZT5y1hBc5dAWVIpjVIXHkCrSyjlsyoJTMqzLX+V2FGk5uJ6Xgse+N02EQG4tY/BM/BnVA5ObSO0AKB4JK0K2WksezatatOaNWYMWNq1RC4mKqqKqqqqmp+FxcXA8pYtcFgaBE5G8r547e2HNcz18M16PbQgJr/ZdlAW2rq+fOe8edRzFUyJlmNGRUmWZnMsgqjWflfW1WNQ4EKsySTmCKzt0xF1SmJQWMMIv3HZTAYDMiyjNlsxmw211l+3s3w/DqCa09buwZmsxlZljEYDKgv8mBv6LuyQysjmZmZuLu715rn7u5OcXExFRUV9SaneeWVV3jhhRfqzF+3bh1WVlYtJmtjWL9+fWuLcN0jrkHrUjTK/pLLNJx/sdlRTFTNPA/SgDRSUiAlpeVlbK9oNBo8PDwoKSmpqc9SHyUlJddQKkF9tJVrUFVVRUVFBVu3bsVoNNZaVl5e3qB9dGhlpCk8/fTTPPbYYzW/i4uL8fX1ZfTo0W0immb9+vWMGjVKRBK0EuIatC6NPf9GI/UMMwkuh8lkIjExEZVKVe87T5ZlSkpKsLW1rannIri2tLVrkJeXh6WlJSNGjKhjGTk/unAlOvRj6uHhQVZWVq15WVlZ2NnZXTJlr4WFRb3pd7VabZvpfNqSLNcrta6BLCvp0/9KNW0yKXXTbGxaUcAOTkOfAfGYNB6tVoujoyO5ubmoVCqsrKxqdXhms5nq6mqqqqraRFjp9UhbuQayLFNeXk5ubi6Ojo71hoI3tK/q0MpIv379WL16da1569evr6mKKBA0mfR0OHcOUlLIOJbLDu8Z5KqsKSlRfBFmzBDKyPXI7sd/QS4tw6azJ86RXrhFeaJxd67toGI0Kr/bcHY4Dw8PALKzs+ssk2W5Zpi7LXyVX4+0tWvg4OBQc880lXaljJSWlpKQkFDzOykpicOHD+Pk5ISfnx9PP/00586d45tvvgHg3nvv5f333+fJJ5/kzjvv5M8//+Tnn39m1apVrdUEQUfhm2/AZKLSrCOh62yOn1LKyXt6ws03g/2lXRoEHZiguUPIPJBGwYl00nftRleQha2DCstAT+zDPHHp6one1xXT0uWkBQ3Gf3zb9KSVJAlPT0/c3NzqOCAaDAa2bt3K4MGDhYW2lWhL10Cr1dYZmmkK7UoZ2b9/P8OGDav5fd63Y/bs2SxatIiMjAxSLvBMCwwMZNWqVTz66KO88847+Pj48Pnnn4uwXkHTOXsWgPwSLVnJEpt9bsXF7E3nzqDTweTJYmjgesYt0g23SDegB7IM+Tkm0o/kkHM8g8T96ci/7cNdzsTR1kjW8iVkLt1ByD0jcO4d3CaVErVaXaejUavVGI1G9Hp9q3eE1ysd8Rq0K2Vk6NChXC57/aJFi+rd5tChQy0oleC6oKCA6t/XkbYnGUaFsUJ7IxHjZWZNCcDBAXJzwdm5TfYnglZCksDZTY3zKA8Y5QF0p7QUcn7fTenqbRTpbagusCL57eN4joJet4TQhOrzAkGHoF0pIwLBNae6mtxl28hZuZvjRFLe/x4c2MIdz/phaaWrWU2UiRc0BBsbsJnRm8NhfdHngoNeqfCr10N+Pnh7t7aEAkHrIJQRgeASZO1LIen1X8g1OaKbNJdBY71wdjawejVotMIEImgiKhXR0a0thEDQthDKiEBwCSy9nbCaOoaRUyPQWyrKR1vKRioQCAQdBaGMCASXwM7Lhm63Rra2GAKBQNDhERlrBAKBQCAQtCpCGREIBM1PXBycOqWEQufkQGmpkppW0GGoLqvm2Ke7MJSLsUvB1SOGaQQCQbNxLk3GrjoXm1NxSIcO/r3A3x9GjxbhIh2I8uwyCrYeY8fKnbjPHErozd1RacT3raBpCGVEIBA0nYoKSEvDdDaN8vg0inelEZdmosLRC08DaN2dcL99FG6DwzpEEpbSjBIy96bg0MkVx2An1Ba1X6FGI6hUytTRcQh0ZNA3d3HmtxOc+/ZPslfswnvWCIInhCGpJFGkUNAoxK0iEFyPmM2KIqHRQD2FIS9Hwk8HqDydgjklDVN2HoUqJ7J1PpQ6hGIKGkFGgDsWxjKs7WMJu70nbt5ttwZLYylJKyL9lx2kZeWAyYTa1QmdtyuWfq7YBinTks0uDAo6R7juDKr+fcHKqrXFbjEklUTIlEgCx4cT98NB0j5ZxblfdhA4fyRbzgZw89BMtL5XV7PkailMKiB9RxLht3ZHUrV/hbijIpQRgaCDI8tw/EAV6t+WQVYW5rIKqKzEY1x3XGaNb/T+sg+mYbayQzNoDFadvAnysqaHA9jaQlKSMvXubYedXZ/mb8w1JPtIBoaSSpyCHbF0twOVCs9ePnh+dzdmk0xRShF5p3IojU+nNK2AvH1nkLNyCDUaSLWwo1RVhO/y3bhP7I16YL+aqs4dEbVOTZfZvQiZHkXsV7tJfPkHrKz8OLQmh+5PjUHbLbzVZKvIKSX3p41s359Ej+dvwNqpccq34NoglBGBoINTlVtCyaaj5O7IQldWgKTVYDF9MsXh3bEHGlvZov9rky+5LDhYmToCGTsSyVu7H6moEJ2FhMbVAQsPR6y8nbD1c8Q+wJH4TEcC5Uoie5rRPHoDR7I8+HNFMV0yN2Gdc5iyIgN5m4/hmpOFNGK4UkmxA6Oz0eF722B2VsXgue1nytMLOb7wFyL+dSO6qC6tIpNnb18cvriXYwuXsuvOTwn65wyC+rm3iiyCSyOUEYGgA2I2mEjdeJrMNYeoPnwSG3UF+VnuBBWfpiKkK+VxaUTdEoFWq7vyzq5TohYMgAUDqCg1kZdYREFSAaUpBeSmFVB1KBU5/yiWlQVkGqvI14Hv2qOE9Q0i6rb+oOsBNoOV8s3NUNG0PeHkBPcuUFEa7EtRrJqKxHTS31mC32M3oopsHYXE0s2WXu/NIuGLLaQ8/zkZk8bRe7wLWjdHxaQnaHWEMiIQdCByT2aTsuIQJTuOYlJrsewTherGMEq3bsejNAfZORjtkAEMe3oQOgsxft4QLG3U+HRzwqebU808WYaVK+H3jWZGpXyBRl9Nmp0LRZWuhBWXown17NDDMldCsrLEdupIbKeinKz8fMjMhOpqpbx1a8ikVtHp7mG49vQn7pWl7N2sJmKIMw4P3IEsqTqCf3W7RigjAkEH4OzGBFK+3oQpPQtdVDh2N42mPK2A0h2HsbU04tEvBNfOFcR2mU7vW0PEi/cSbLr5E6rNGgxW9his7DFaK5PJ2g6jtT1YWqLBiO+JP0i37IGNjSeHe9xJSKia8HDo1Bk0wiWhNpKklLR2dm5tSQBw6OZHz1s6kbLiMEeXF+Ok2U5x9GC6dVMKGQpaB6GMCAQdALVei/3gKNDrydt6HMO3v2HTNZCQf4zBfVBnKC9HNgyhj5Nja4vapol4fCzmgiIo+msqTkAqLoL0IqisxKzWYrS2RyovxvrUAbxUPlR064ODbResrdXX24hM+0SjQT18KIEuTthvOkLcb5vYl+DP6dP+zJp1fYRlt0WEMiIQtHMKEgvI3J5AybbDaLQS7qN6EPjiBCw97P9eydYWYQy5Mm69/C+9sKpKUVCysjAv/RWtJBHpX47e/yS4VUNAd9GTtRccHGDwYCx7DuLsh+ewPZnM2UQfNmxQM3p0awt3fSKUEYGgnZP0y34M6XmEPDYJnyHBSGrRIbYIFhbg5gZqNaq75uPu6tpq/g+C5sHSSuLGR3xITPTh+HE4cAB8fKBL6/jZXtcIZUQgaOd0/8fI5knmVFoK27crTobnJ3t7GDEC9Pqr338zk5QEu3YpJW+MRmWKjoaePVs42Wsb8X0QNA8aDXTurExGI6SkKD63wq/q2iKUEYGgndMsiojRCGlpcPo0xcn5yDKoe8dgOWI0an1jM5G0POfOKbX4EhKUZLJWVjBpEoSFtbZkgvaMRgNBQa0txfWJUEYEgusVsxmSk+HYMYiNRbbQU+nqS/7JclapJ5ET1wXpNXB0hFGjlI6+tb4WZVnRlY4fV37//LPyJRscDBbFOUxw2IFluR/k+imWC/FZWy/lueUkr4ml801RaPTi9S9oO4i7USBoILKsfJG3a/5qhOnIccr3HqekWCbTOYJE69tIrPZBPlaAQ9BICqrt0QC9esHAga2XMuPcySJOHyghKbYSc3klwX7lVAfDQ902ozdWUVRRgZ11JVJCMsQdVjaytobBgxXhhUNpLUrPFZH7+26yf96M44T+hN4ag95O+L0IWh+hjAgEl8FkguTjpWRsOEFctiO2MYGNrSvXZjj92RYqdx+mIq+cs1bh5HpOxaJLIO6eKgI8oK8HuLkpib3+/BMGDGj95JSZ32/ENT2RCF89Ll30mKz0rMYWtbEKLC2xD3dU/FnSzykRElFR0K2b8r+gDm5Rnrj+sIDktXGc+2Eru5ZvxXZUX8Jm9cbG1bK1xRNcxwhlRCCoj4oK5JOxnFl2nHPbkyh0DKR65O1MmGBiw4bWFq5pFJepMQ4YhW2PTozw1eLkdOnRjLFjr61slyLmP9Nq/TYZDLB6NYwZA9q/fFkqK5UoFx+fSzbIXGVApVH9nZrdbK5rNamqUoasunTp8JV2A8eFETg2lHM7kkj5div7bt2B5eBedJ7VFyd/WygsxGTrIPKmCK4ZQhkRCOqjtJSylX9ScqQUk5UdyTHTmXOrCp3O1NqSNZmejwz8+4fZDFIHGcLQ68HXt+Zn0dlCVLIJnaUanaUaSa3i4KsbMOzaj95Oh97BgpLsCnyqEzmn9qPUNYgCyZHQrhZ45h7D3nIN6tBOipWlUyfFq7EFyDp4joK98QSNC0Xn53Ht/VwkCe+BQXgPDCLnYCpJ327jyJ3voO3dna6OaWxnICMfjmi3lkBB+0IoIwLBRZiLSjjz7hqSDmoJdLfA464bCfawxtERDIbWlq4JnD6tOKoWFytJuyoqYMwYyr07UVAAXl4dy9/z6H9WYohPRiUriqNaDZjNGCqMFOdUUV1RSGmpmfhyG3Smc1hYpFFp4cy246H0DaqmSycT6jNnFEtJcbESK9wCJoLqakg9kE3Wsp14BOjxHh6KTUwoBAS0mAJ0KVx7+OLa41aK4jJJ+mw9R/7IwMq8hFX5ZYx+rrdIky5ocYQyIhBcQOHe08S/sZws2xC6vT0TP/U5CPJrbbGajtmsKCA7d1JaCml5epI9+5H3bh5SWTLDe5UgBVnDsGEdJoHXoE/vwGyGg4uOcu5QFgXFakrKVKg0KvRWKvRWagoTcumcuZUMORCbkkTK3MNRhYUTa9GJeNcQBtzoiZdvy45R+Pb1xqfPDFISjRz/PZmDK+MIX/UbAR6V2MeEIIWFKpaZw4cVBcXLq0XlAbAPcSVsgAt708swZ+bhtHs1a/9ZytAXhuHs0oE0VkGbQygjAgEgG4zEf7iec6sPo75hPKPvifqrb26nSQfKy+HAAeS9+4iNU5Fb4U1VtcQv1ZPoe/gnAmzz6NkT7Jy7dChF5DwqFTg7mnEMrsTW0oidpQELlQHJZKSq1ECBTQmOjt6YjWaqc93QalOxsEhF7WgHo13Bx/uayClJ4B+swf/hEAoLQ9i7ZzzbtmTivyeO7sd346VeQVquHl/XDagGDVSihFrSaqJWo586joGToahQpvBsEY5JecTuLaH3SLuOdpsI2hBCGRFc9xSfyeHki0soqdAQ8vI9BMY4XXmjtkpWFuzZQ/X+o+RY+HDaaTxbPTtTtmU/+rxzTLT5DJW3E33CwfqGYUrn1pHGaC4gcGo0EF1nvgXgcf5HYiKWO3ZAYKCS7crDo9XCgR0cYPQYiaHDPDl82JPle4aiy0wh/NQiijPMdDFuRX3qFEyZ0uJWEpUKHJ0kHJ0coLtDix5LIAChjAiuY2SzzOkfD5Lx9Vp0A3oz6PFh6K3bYfiA2UzV0Tjy1+yh5FQaZ6y6ccLmLoxaJyx2nyAk9Uusy7LoMqcb3pPvpFprhXVFhkhXCn8rIW0InQ5691bSpCz/ypb95XORkDliCZMGydiZTCJfuaDDIZQRwXWLbJbJ3ZeI3z9uJmhk2+qQGopsMrN3zocUZldTEt4bq4kzsFJVErFtPxY7DuEVYo3nU73Q97kdC3ulvoySv8z+crttOCaT4tWrUimd4/np/O+2ThuW0WSCbkMc8YtypKhIcf1ZF6dkw7Vvu2ILBE1CKCOC6xaVRsWA/93U2mJcFZJahft90wjv4oGdg4pD722neMUmfPqFEvLfGViGB7Rsh2swwGefQV7e3/NiYpQesw0W12trHHhlHRXpBdj3Dcd3RGccPP4+Z2q1ku5eILgeEMqIQNDOCej/t/9A0KQItDOisHJvwdSpBgMkJ5OzMx5N4mlszEVo1YCTk1KtLiCg5Y7dwQiY2p309ScoXbuDQ1+swOgXhG3vcDyHhmLvZc2uXTBiqAmdvp1YmgSCJiKUEYGgA2Hv79gyOy4ogPh4zHHxVMclUaGy5pxFZ7blj0djrMRNzqI6aCg9DVo6tYwEHRLnMFecw4YCQ6k8l0fGn7EU7jpA6vLfOWbvT4ZDOF/v9WGSw1bc509svSJBAkELI5QRgUBwSRKXHKR47S7MuXnkWvpxzqoTuY6jUHu4YmcvkWcAjWTCo1s3hvYFT8/Wlrj9ovd2JvCOgXDHQOTCIv78IBbXvSewT/iDWNlMzsFUQh6diD5aOB4LOh5CGREIBJdEtrPHMHAYurAgOrvr6WUPdnaKP0NurlLKpVcvddvP0JmWpsTOtnlBFWQ7eyLn90W6sxf6pd+jSUkEylD9/COc7a4UDxJ52gUdCKGMCASCSxI8OphL+VC6uCj50lobQ3EFRYcScXIClSTXWiabZcXVIjkZDhwAb28IDYXOncHdvc36YahUinjIKrjnFiWTrsmkTGazMjUjxz/fjZSfR5cFQ5FsxFCQ4NojlBGBoDkR+R+uOXkpZRx4exeSpPjQOjlLODqCoxMcPaKkEXHQVyornzv3d42enj3b/riSJP1dnbgFce4TwuHXE6me9x7h9wxGP7j3Na+PI7i+EXebQHC1GI0QF6cUpBsxQhnHEFwzPCJdGLd0PllZkJICR1KUv2WZoPIEUykMZT+9+5RiGdVZUUDascJoNpqJX3mKwLGh6CybJ0mfZ1cXHD+7lQ2fnCH/g7V037YfpxmjlMR47fhcCdoPQhkRCJqCLP/V8x2BEyegshJmzhSKyFUgy0pBYSurxm+rUik6hqcn9Omj7OvkSfjlF2X5ppKe7D8Jo30g0hPac/daklZE9uINpH22Bv2gXgTeGINniPVV6wx6PUx4KJi9ve9l+bcHGfbe7wT02oM0doxyYk2mFqleLBCAUEYEgqYhSVBaqvghgJK/Ozwcs1kZBbC2vibW9XaP2QypqXDqFCQlwY03NkIZucyQmCQp5VseekjpZPX6Vis50+zYBzgy8McHyNoeT8ay3cQv2MrhoK64T+5L+FB3rKwU52Jn58YbNSQJ+vRT4ePXk2U/diUsbhuDk79E1z0C/P2VHDPdu7dMwwTXNUIZEQiaQkICrFxJhWcQcUcqOJIxmoK3FUVk6FAYNKi1BWz7nDwJq1ZBWZnSCd5yi+IU2xBkGaUy8Q8/KBv5+CiTm1uN1uHYQilX2gSShMeQUDyGhFKdmkXa0j0UfPYZ6z/3xWJwHwrdOuN89iCDH43BQt94k4m3N8y/34LffhvJp3ExzEzfgOvhFZhMtIh1RLhaCYQyIhA0BpNJ+btiBfK48WTqw9hfWEJaqgaNBqZNg8jI1hWxPSDLUFWlTKC42nTuXHsdQ2kV5/6MQ1NdjtZQjrqqHNlYAa46ts35Ah+bMjzsyrCzTkM6fFgxR/XsCQMHdniz1K6HfsDCw5FOd/TFzt+doEcmwd0jCd54gOzfV5G4di3qqhI2JKbR+6WJuHo0XoHQ6+Gmm2DfPkeWfxvKqLJYigrMhKpXQ/duzdaW8uxS9j71K4EPTMC/h3Oz7VfQvhDKiODaI8tQWFjz6VpZCSUl4OraumJdkcJCWLoUXFyI7TOHnbs8KCqCqChn8o/CzTeDn19rC9n2KSmBlSshIwMmToT4eBgQWQTLNyk+Nw4OYG9PZbmapJ/2UqW1oUptRZXaimoLB2xH5pFXoiNNCsIj+Sg6P08iZ/XAdUDnK361Z2fD7t+y8e1sSUBX26u2nuSfziV17UlcY/xw7+GNWq8oQWaz4tes013d/i9FwOwhJC7excE738eqRyjBt/XDOdoXh4mDyAruj+17P6BPK8Aq9TAHHi7A94mZRPRqvDOOJCkjkD4+3Vj8VSja7HOUWqUARXD2LISEXHVb9E5WeES5k/j0Z5yZOo3+czqLskbXIUIZEVxbiopg9Wrk6O6klzuyf7/iKzB/fmsLdgVOnaL6lxWc0oWDi8zWE8706QNRUcri3r2VsFJQmmilqkQbf1IZMoiOrneX15VpuroafvyR9PgyDp/SE+JtwfR+lujUnYnwKkPanq04jlT+FYLr6Ihtv34MfXsKxpIKjEVlmIpKqSoqYTugKS7AJfMs7q7VOOsM6DJdkA1BSGo16fvOkfLHSYxoMJjVNX8NsgajrKY0tQDb77ay1d6XUr8uaLp1YcItdlhSgdpar2gRGk2DLo6h3EDZmUzy/9hLfFUFWj9PbCP8cIr2448TvvQeZk1k4Xak7tHNmnDNq5c3Xr1uJO9MIXHf7uHIP77DOtAV3xn9CR0UTOhDMZDtq5zPoiJMSWuQw8Yg2TZNhqoqsHK0INsQxMZKX6JY3Wyat0qjIuzhMXj19OLM20tYfnQg3R8aRGjY9fJwCEAoI4JrhdkM+/fDhg0UGGz4ubAzGVnKoptvbsOJMU0mCpdsIGPVQbbZ34BFzzAcWM3dd9f+6nVygrwcM4eWnMEq4Qj9HU8plp+77qq1O1mG1NMVJK+NwzvGg+ABHte4QdeQ6mol82lKCqakFM78sh9DZgEDnMqwt3WAIx5wLgmNm5uS4cvdXXG6GTyY7a/twLxiNSazhEFnTbXOhmqtNSZbG3TTVVi6WqPLryTWPoZyjxgCnLzoWSVhrwcVZixU1VjL5Wi0JjSyEY1kojI5k8rYM+Sfq8SlIA4PGz26RCtydvqwelV/cirtGOBwguDJkdhmxkPfvooiaWl5ySa6R3vi/vYMZLNMTnwhWftSKDyWQuZ7GwkqzCX1D2cqbSsJC9mG7fjBSqhPM+bvcA52oP/CMZTkDCH2+4Oc/N9aUr6Q8JzSF7/qVKp6DUQVFHDVFprAQLjvPsjKgsOHFeWksEhqVmum3YCuRAe54vbfH9n/QjonJk1lzCQLrK2V44mEsx0boYwIWh6zGdasgX37AFAP6kfZEcXJMDpaSWXQVjn28kpS92Ui33g3k0Y74+xsYPXq2h/N2dmwbRvE7yum28mNDOySCWiU0JC/eoHslEoSfj9F4Y4T6NMTsendheAHo1qnUS2EsbAUKTUFVVoKUmoKZGaCjQ05ln6cKAnD0TaNMH8VFpNuhS5dFGfTCzv65GTw9QW1mrAX/cHCAq2dJVoLFVqt0ocbjQZWr16N7Zj+VHp2ZkgPfZ20IR69fPHo5VtHvpwT2ZxZdQrrw4cxx8sUGnVUG1RUZpThlrIMf3MZSNWkb/kDewcJqzU7sOkWiKp/P8UXxdf30tE7Kgm3UEfcQh2BKPbsgZ0byvEoisPt5ArOnADf4vU4HzgAo0crWWCb0Sxm66qn9yP9qbyrDyeXxhL38w6yKzNw3pTEQe9JjP1n1FUr/JIEHh6Kf8/q1S0TnSR5euD9wt04fbeUk+s+48tTNzNgsgvHjsHtt4vI4o6MUEYELY9KpZgO9Hry8iW+3BNNRLTyETxuXGsLd3m8bhuG//3WpKRrsLevf528PDh5zERA2h7CPQrQu9goedLd3WvWscpOxrxiJVZVJlSe7nR/fmKHG6M59N52snYnUezgR5lzX8qd/TBjj9ogkV8O2uAI1tpbEW6U6CqDv/6ifB8BATX/unR2uuyxes8OR6drnJOqa4QbrhFuwOCaeTk5Sq46Kys49skOOlUdR2cP2vxYNN3DkLp1Bh9vxcrViOvVpw/06WMF6e5QOOPv+OLzUwuht1bT4/YumBzOkrG+gLOnKnFJXMYfBQUMWzgEZ5fmu+daLKWOlRWW828jJnAjPqs/Y/l305BKS1hl34OJk1Ut9tgYqsxoLTpI/Hc7RCgjgpYnNhb5z00ciJzNvk2ljBynpXt3xYrfUg5+zUWZxp61is8qkREyBmPt5aWlsGtNISNSllBlNOL70t1QUgDBf1d0yTiWy8k3tmLnbAPFVUT8eyZa6zbe8CYQ9eQYqqoljEYlHcX5v+npsHYtOPpYExiopGf38Lg6Xay5OiRXV2Wqrobo9/siaQYoYwI6XfMcxMtLma4lKhXqSRPQ9Z1A0ooKytIKMOYW8v37BUyb74SPz7UVp0moVDBqFNUmL7q+v5SKcpmzKyrY5TaI/v2b/3CFcVns/+cv+D93B516XuKrQ9CiCGVE0LKcO4dpyTI22k3l+BlvZv5DyWEALa+IXI2DaEEBbNigJFe1Lc/iZuu9UDRICR/9i/x8+P3NU/ROWU74TZEU9xuDxk0L7kp4otkkc+TLAxT+vA73sTFELBhCweGzOAZf/qu/vaKzkNDVM65vbQ1du7ZhvyDO34t/jQF0EOcENze4/S5LwBKDwYv8fCWSyWxuPwngfHu44jvSivL0QjoXbGLPgRDiXT3p1Kl5j+PQ2Y2QEf6cfuEbUubPZegNNmJI6BojlBFBy1FQQPnni1lbNowC73DunnFtOiSDAXZsMRIVWNzkjt9skik5dIZusbuI0J/B9obhSsipwQBAVoaJ3S9upK/pEJ3+ORGpayQXRokWZ5Rx+MXfkDLSCV84E48BiqXEqV/oVbau/dHQRGaCK1NwJh+tlRYbT9tGbafV/u0j3K5wc4M5c7A6eBCrgwfxVf2Kye8emr3rkiQC7p+Ak+1yDv/wDd+kzWHa7VaXHJoVND9CGRG0DBUV5L7zPZvORmA1vS+zx7W885ksQ9wpmX2LThCeswXH/93e5P0c/vk04cd/xVpThV9PNxgwoNY6R//xHdG+RoKfuhvJpXaipoQ18aS+vwKbcF+6fXUfFo5NKLYiENTD2d+PUbhyG9b9o+g0uz8OwX9Z4dqRtaPRODjA8OEwZAicPo06JYlmN40AqFTYzZpCf90SHHZ8y2fvzWbSDH2dZHyClkEoI4JmRzaaSPj3T5yIdyL4ybH06NnyjpoFBbD5mxTUG9fhW5xG4N39aMpnjSzD6lUyFbGZDOgOakmDdsbEGk0qOzYXgOABHoQsGFsrTNNQbuDQ6+sp33UYn3nj6HRTdIdzUr0qOnBilfISE3prdb0KQVKSoij4+V1986MfHkL2iHDOfLODw3d/iGV0Z4JuH8DmBB8mTeowI0z1o1ZDeHjLHkOlQjNzOt3kH3GM/57vf7yDmH46hg+v+zElm2XMRjNqnRjPaQ6EMiJods5tSSDpdDU9X7sVn6Br87lmLxXjfmIj1cVp2LvqcJ48sNH7kGVYt8aE6deVTAhORD//TqXimO/fYaIunZwgCYLuG1MnX8TBl/+gOjWL7h/fi31gG/MLaSVFQC4sgoQEJK0GzpyBHTuUcF43N2XMrndviIhQZCsqgmXLMFhYo3F2QHJ0UBTKgIBmdTCSZZBOHFeiWoKCrt6kYDaz+6a3KLFwocw9iGrvQMxePljaqLGyAlNJOUfjLXF2kejeXQlnv5rhSrdIN9xen0pB8nBOf7Ob409+g9bKk2WnBjJxnhvWheeU0Ok2jKnSUJOtts2hVsPMmfh+/z33Fy9m5fZ+/BDrysTZTuTm/u2bfvDNPzEVFNPrP1OQVB1Tyb6WCGVE0Oz4jAjFtW8wFtbX7vbavbkSY3oO3t3dsO0dXsvRtKFsXVWC3Ttv0G2wPZYP3qXELl40yK7SXLrj6vboCCzsLFBpr/ylZDZDbKxSj0VblPt3+DNKyPOZM0qn1RD9wWiElLMyvj6yEppoNCrZqc6dU6byciXveovFYl6C8nLMh44Q/+8f0RVkYW0sQqvXYA4OwcYjAP2gQYozw/79SrKW7GzktHNUFRnZdxQ0nYPQjxmCl5OuTgXaY8cU672dnTLVp6sceWsDVQdPYOmgw9pRh62jFhsnHeh0HN9ZTLhlMjbu1ooyFBl52Twil0WlYtA3d1EZm4jxdBLmM/swHjdQ6uRHkXMQWdkS0UdOEd95AjvK3UhJUYopXm2QjWOAPd3+MYbFToNRHdiH99bl7D+ko1fnQqymjFGStrVBZLPMjvu+w62XP2H3DWub1jKNBm65BdvvvmNm3s8cyIjkk0+mAjBpkpIbKeTW3hy87zNiP91Gl3sHX2GHgishlBFBi9AYReRqP9oPb8il8tNviJ7fG4chUaisL50xs14MBo6+uxnPrz7Eu78/3P8s2DXe3m3pfGXfEJMJjh6FPeuLidGfQLvjmPIlNmcOeXmK4eDIEZgzvQRp/ykl7vSC/BugnK/8PJmkQ4Vk70mi/GQSXXtZon14rKLlrFoFhw4pKzs4wJw510YRMZko23+SnO/Xo4o9jib9LEXVVpRYuqHSOHGg8wzcrUrQFOeh21aAat33VOjsKLV0o1jvRpFFdxzPabAtzaDQIZBcUxgVmzRYnS6n12BLoqIlsv7K2nvks73Y5KRRYudNpbM3MRO96DXQopaRw2tiDFmdgynINnA2p5qi9GoqYqvRqw3YZJdQVgDObpX4aLJwtLRUko000dtW6+aI1i0GhsQoFyg7G/ekJEhMJD0uGZVnNaPVH2MZ3Rdp2NBms/RYWsLsey0pKBhMfkoPtF99Sma6jPsPv5H562E8n78bK5u25UwiqSSCHrqB2P9bjKYwl5B/TG2bhQ3Ly6G8HDUmIs1HOWwcRHq1CytWgKcn2PvY0vmF2zj91JfY+jviO65ra0vcrhHKiKBVyc5WPt67d2/a9nE788j979d0vb07TlOHNF6rSU4m9cUvsd6yG62vOz+HL2SaumUG3o8ehU2bwOLkIbomr6RHbzPYWmGcfy+rV6mJ3VmAS04sN1jG4vtLmvL51bNnnf1UF5SR8MyPVJxOxQrwjfEn9MHJIMtU7TpIzqZ45HI1BgsbzsXMwXjIgd69m2QsajAnXliC5kwchgoj+amlFPkPp3RQb7JtQ0jfFEeJ3pWBk50JGWCg8MAZTHprJHc3rG31eGllLEzl6IpyOPKrF5W5dlgfOkRg8REczbnIp/WkHYrkV5MLelU5zLAmIHsvmsIiYqxi8dWB9rQPBIyuVS/FtbMjrp1rV8KrrlYMMUe+sSM1cDBqfx/sXbT08obOzRX1I0l/h6706IGX8UdlCEqrhdQUJX3piBFg27iImEuh0fyVL8USeOgGyMujcG8cLF7H0dFxFNz+IF0mBNX4rDRW+S9MLiR5WyoRN3dtNp3Bp7srvDWfI8/8hPr5rwh85pZmOx/NhoMD3H037NiBxbYdjLPczPbAG4mPhyVLYO5c8O7hTuH9N5H09k/YeNnjGCUqZTYVoYwIWgWzGfasLWDrLh1zH2haL3n2cAEp//6asOldcb9leJPMK1uW5mK3Zj8GZx9OBMym1yiHFgvnc3KCkkITDhX5BAeDWiPBtGmoHe2wsQGNoYKQtM1ExFSDqxtMmVKnTSYTHPkjnaJzpVhrwcLPnYgXb1ZK327YgLEMdjpOoLQol2zHSOzTHJg+vZkVkdOnlbGk6molQVhVFZKLE1ld5lNh64bJLIEJLE1glQOaruG4aaGoGI6f1tF9cDiuLjIH/vUbFTm5SLm5yOUVlKrsKNG6UGzhgretljyTNbnlOpyjOtPJ1USfgiNogr1ZgzXOQyMJy9+PrlcUxMQ0OGZVp1OGxiJfj8LW9hqMEOh0MGtWCx/kL2xsOB/64dCvH9ZzZqD+fDVOe3/k8PZg1keNJGKwMyEhsHu3kv24IWVyqrIKqVy2htXrT+MxbwLdejePw6ZPqDXym7PY+38rUf/fZ/g9dauSDa8todPBsGGoe/TA988/uWVANmWT3Dh2TKnr2KULREwOYdfZ0Zz814/EfDAPvZdT2xx6auMIZURwzcnJltn23mG0h/biPv1u3Nwav4+M2ELin/uaoPHh+N45qkkPf8WZc3h89hInI2+g2DMUxwn9iYxsvCwNIT0dln5ewLTipZRpqnF/cjYkJSIHh/DHH5CyI5WZ6mUYezijsytQqgdeFBqRdryQk//9A7v8ZKLuG0F5fBo+w0Op/HIxWacKOGw/hBMWPfDyVZNilunXX2LEiGaty4apyoiUkoZq+1Zlhk4HN9xAl7Hd6l1/3z7o1Utx+qv94SshuTijCQ5E4+mC3ssZTwcL4k6aKD2aja+1joCeruiqSqjKLqI6pwirahWGjHRwcyW8YBfaoUNg4MBGx4xfL3lPso5lk/xHHLbdAhjRBUoPfcTRX3ryuc0QqiUL8s6WM22WzRVH8Nz7BOC26D4yPlpO0vsf813YJNx6Kq5JV2sp8Q3UIL0yhU0vbWfoC1/i+/C0tlmsyt4epk4FgwFrbV13nD4P9GJTWj7HnllMzLzumDqHo/Vwrn9fgnoRyojgmiKXlVO+aCXO22NJCBxFvz6NVyLyk4s5+dTXeA3pRPD9Y5v2FZKRQeUXizkyYAHaCaOpyIKZExuxn6IipTx7A3JrJyfD+rdPMLlyJQE3RFI9bAyStRajtx/Lfjah3rqZWY670U8cgtyvP6SerXFmBagqM3Lg/V1Ub9iKz7AIQh94kPLccor2nebwwuWcdOiPZnB/ukTrGBsGFRVQUCBdmJH+6pBlSEmBo0eRj51k50ELMFijdrCjYMSN2BY606ui/uK2vXpderc9Hqob8ZT25UaCdu6mwNGW0uN26Fzt0bnaseNYMN3KsvEO+6uuyxNPKD4egkviMzAA688f4MT/1nPgl9N4johkiG0GqqXvkurdF5f9J/myeDZTb7PC3//y+5LsbPF68nY8d+8h8Jef2EcXPvnIxMDBSmmHo0ebPtTq4ysx7PlBrHnLmTFv/0pZr6GEDfVA8vRoe9f4EtqXSgUD/m84O+9KJuHjDeQHF9H3pQnXWLj2jVBGBNeOkhL47nvKD2RibafGsl80oY1MSFpdZuDo41/j1COQ8MfHN0kRkVNSSX31ezYZBhJ+z0B69VJqzDSoflmukmeEb75RaqpfgdPHqzny2h+MdziJ90OToEsXdCijG8s/ycZrzzJ69waLm+eDu7tSOC4wsGb7M+vOcPaj1VjZaYh6846aMenkn46RXeKA02OTuSnGptY729Kyli7TZCpTcyjadpTq/UcpK6gmzT6CeMtbyIrwxSvjAFme0UQ7augWXIZlaTkUmZRxJJNJGYfz86sJm5VlZXZ1tXKeKysVJ1wkqdYl7Hz3UEruGElhsYqCAigsVHLIpLibKSzyoMToSRRriE3Q0rWrsIZfCUd/ewa+fSNJm8+S9NEfZJkqOOfSjZG2e7CxLaV7xTekp8zBzU1frzJZC0lC6tcXVz9f2L+faaXfsW7jVLZvd6a8yEBBgZZhTQyO8fGBcY93YfkH9oT+/AOOJ2Ula/G0aU1qd2ugKcrDzxfS9oE56zDFWcOxc2+kM/11jFBGBNcOGxtO5ziSU1ZMr5sCiJxp3eisrDprLUEPjMd3SFCTYvurTyVy+sUfOew6iuFP96pJIXJF37n8fFi3TvGXiIpSskFe4e19clMWqf/9hQF9rPB68L6aJGylxWY2vLiT0LNbiJjXF+2oofUONex5fhWVe4/ic9twOt3aC0n9d1RE5Py+LdoRywYjO+75mjJnf8yR49GPCMHdS024m1Kvp7q6JzMGKj5+5JSTvvBTMlMNqNVgsnMkr+94LD3yOH5SRUWVimqjCpVGxciJlkT31GAywdLvKwna8S1qUzVYW9Oltw1e0Y44DeiPf+Df2tXp02Bnp8LV1R9nZwMJCRAaKhSRxhA41B+Hrnex4sUjBB76ldyETByjrPDOP4P3KTX0ngU00HH7r3FVz17ezD3wCb+VjsV8IpZtppuprlYzZkzTrk1FBZRbOFJm6ULyiWTcrI+i6tq13myrsslc63loC6i9Pai4/S7SynbjeWoTCT8dqNf6J6gfoYwIrhkpP+wgZU86kW/ejaVtKTSxkrrfsKaNPxTuiSPuP0vIiLmBKY9HNS7xlL09lJX9/burEsaXl6d88V/s95K2L4Psl78kcnZ/vG4dUmMhKM4oY+9jPxJgXU7XN2ahDvDlUniPjsDx/iFYu9cVtFEv+6oqyMhQPj8b6EAiaTUM+OVR9NZ1lSRXV9DJVVQfP03m9pOUHk6goFCirBjSPWPICBtDsL0RpyUfE55ejCyDlZ0Gz5sGkJ0axKqVWZTFp9OlMh1NSQ6uLjKdQvOxiOgJ/frWMc137lzjl4nBAAkJHTj1eQui1qqIntudswO6kPvnVsoSdxHTSYul0QgnTzY8sc15Ro7E6NeJgV8uocyuEhfjBo7Gj8FggAkTGn+NOnWC+Q9ZsXXlVE5v3Id3/gF8V66E+++v5T9VkFjAsWcWE/3qLdgFtJ3kgpIEXaNUBLzWn7U/hFGyYwtR1SaRobWBCGVEcE3I23uGpEVb8PnnXDzDHQCHa3r85JXHOPv+b6imT2PivPDGWWSqq+Hnn5WesNtfjpqSRGIiLFsGDz5YdxPvGA+s/jcXp8jama2sXSzxGRlG6O29kCwun2vCZ2BAI4S8gIoKSEigKiEVKTUFXWE2TJ5cJ1/JlahRRP4qfFJdUkX6plMU7zpJ9ckEsk3OlAd0wXrIUPw5y/7NZtRqicB9P+O5KxlnDxX23lDuFkBBailnvtqGndtewsO8cLvZm0xVGNrMVPwdipBGDG+esaX6OH1aKRXdkrHN7QA7O0XfiI62QI4OoOL7A1QW2mCZlaUo2k0wZ1hYqnD11eNqW0kAuxgy3AdD54gm18pxcoIps+3JGD2SPduH4O5zFN2RI0qm3r9wCHBAGxrM0ce/pse7c7DydrzMHq89trYw/S4njvaeQlKSmZDrrzZmkxDKiKDFqcgo5NS/l6CfPoHwEVeZdrKJVFeDx0MzCZ0Q0rgNy8pg8WIlamTOHMUMsmED+/fD+vXK15xOhzL/xAll/MDCAkkl1VFEQPk6DZs3oM78q6KyEmN8ElJlBWmu3UmM16L+dg+OZWlKdNCkicrQUgMwJadSEZtMZWYh1VkFlKYX437TYOwHdiU/Po/E73ah694Fh0dGMqCHK7Y2MnsWruHcodNEVJXg3MMfz2khOPUeA+npVJYa0ffvQfqOJFw6OaJzc6jp9GwBKgMa6KxzZfIOJKM+l4KDk0rpCc9PsbGKF7Gfn1LbJCzsr/Gl1kE21/WVudZInTth9a8nscrMVJyTU1KU89TY2i9BQfDww0qyoBMnYNMmtG5uivnsKvD0hCk3aTGZYkAl15ZdJdHn+TFsf9bMkccUhcTC3aFmuakNWCMkCaKiJWRZWEUailBGBC2KqdLA4Wd+whgWSf+7o1tNjs7Tm5AdsaAAvvuOcyYPEoKmUrJBQ0mJASsr+OUX5UszLKgadh2AXbsUq0m3+kNcmxu5oJC8TUfJ2X2GyvhUgnrYs63TPBK+P0tIwh84WVUSHmOJNHyIkoejARQXw7JPy/BZ+gNSZTlmgwn3kV2xTz0OJQF49PDC4+d7L9pKwsbTlsCR43DvG1jb2uPigl6S4ORJvHLioFCrDBNpNEou9PDwZlNEAFLjK4n/LQ8nBzNBAWZ8vc1oVGZMBcVIJhnV2bOK1aikBPr0ufbp8f/i7MYEEj7bhK5Pd1yGdSUgTN86QSMqlXIdvLyuLnW8JClDgD4+MHq04g3eTCgWzLpam0ot0f+lcWx50syRx7+mxztz0DjbU1VSze65n9D5H5Px7NP6CciEX1PDEcqIoOWQZY7853cqDRr6Lxzbvh7MzEz47jtMYREkO4xl0wZFeDs7JWeGiwt4pe+ny9qNYK5QvrQHX5v6FEeOwKY1ejpvOYJVRR4RPfUU9BuP+tvf6ZaeRF6XQXR7oS+arDM0KFzJbCZnexzx3+zCvPkcZeUmvKozcRvZFb+RHkpEg16P2QyJiUp044WhoF0XDKp/vxUVikUiPp68P4+g0YCtkxbV8KEt4oEafXMYnSeFcewYrD0E+WeVsjNR9ps4km/H8Pkh2PrYKwkyGus53Yx49fVDVRpDyZaDlCxcx0qrLhi79cC9lx+dNYl49fPn5GkNDg61Esq2DyTpmmVS1WglBr4ygc2Pr+TYE18T9b85WDjY4TS+L6dfWIz+v3NxDGtYMjxB6yOUEUGLEfvNPooOniH6o3uwsGpH5sqkJCq++pGTTgPZFDsQjVbCxUUJnpk8Wakf07cvdNY6Y7GpStlm3LhmrSx7KWQZpMQzhG35nWqtNd5eFiRXeVL+2k8Ej42idN6DdOtig40D4HB5RcRYVkXSssPk/L6bnLPllEq2+Pqryc/2wWuAF17ju8OECRSXqTm0Bw4eVM7BXXddep/5+85gPJ2IlJQImZlU27tS5h5EeYUzCYWuJFuPxe2MAwEmxSm1uRNuWlkpRo/evRV9cs/SNFbFe1Ot0nPu8yomTC/G360Cli7925J1jS0kOlsL/KbGwNQYyMqi246DFG79kZyfrYjL13LsbRUpfWeQVeVAjx4watQVA7euWyz0EoNen8jmR1egefJrIt+cQ9e5PdmTW86Jp7+jx/t3tjmfkqtFNsvkJhS2thjNjlBGBC2CbJbJ2x5LyDMzcPRrYzUnLkPuztOce/sX9rhMwDY8msk9FUtIfLzyd+tfiUf7u8ShX7lCUULS0hpmgbhKCtLKOPzaWrSJcXjfOILT2giyFr2CNlyix4fzsbKWyN55hBKrMFxcLp/9sTi1iIN3fUSlSUOVrMPJ1kD0IDscx4/hnGUIXqbjEBlJ2jmJH35QXGc0Grj99ssbFQ5/uJMSbClz70dlp0AkO1t0OtCFd+FEiR9qtRIY4eICzi2YoFKSFL8Dh6w4sjbHYS1XYqerJGFjNarOyoiCYfUGtBs2IgUFKjWAwsOvvV3d3R3LaeOwnDQKz4MHkVetpqwMDmz7hOqQGzl4MJhTp2DMGEVvalfWxWuElbXEwNcnsfnRFWif+Rq7UX3oPj2I3fllHHniW3p+NA+tQ8dxXs7cFs+Jt36Hec2V1bBtIJQRQYsgqSQGfDKrSblAWhPJ3Y2KiTOYOalTrRo1oaFKSvc9e5R6FOrVv8P06YozZI8eLSqTbJY5vvgoOd+txb6rH5GL7kftaEe4LHPWPJqqjALi/rWY8sxi8roNY+wEZ+S/fP4u1XnZetuh69UN1e4D+I/qRKfbZ6LxVkzaip3g79Bli7x07AszGRRdguueEsXnIjKyJrz5QoZ/dUe9x4uL8yOk/CrcRGSZhANFnMm1+mt/4OioGDVsbC7dzqEvjSDqsRGcOqVEr+6PNxNvOMOwtGXIvn4kGv3o38MPh1DP1u3pNRpwdEQaMhhVbjmdfMoIr96GIaYawsLRaJon/fq1QjbLVBRVY+XYMkUnL8bOQcWA1yez85GfcXp/FZX9A+j3wiy2PPIrR/7xHTHvzUHSXxtZWhrPwZ0o3uLGKRS3tqaU02iLSLIsy1de7fqluLgYe3t7ioqKsGslh7fzGAwGVq9ezfjx49G2l7dSa2EwKBaLC7KZXg1GI3z6iUw/w5+kBJYyvls3tM2078tRllPOgaeXQE4OgfePx3dUWK1OM3/TEU78exkmg5lSO098BwWSpfHGsndXBg68fP9anl2KJIGla908JiYTrF0Lx47BzTHxSD8sxtdHRtKoYeJEJUb0GlBVBdlZMjkpFci/LCH/dCbl94ZSskyHTYAn0dOCCOjW8OeyogLOnKgkLtmC0/ESVVXK6NqoUYpxRFgerkxD3kMpa2OJ+2ADXk/eTpcBjg0/r40tKXwBGXHFHHv+F3RZqVhYQO/37qDSI4Ad9y/Gy8NM5Cu3NW+hplbEkJfH6u3bKTwYxo1PhrbpqPWG9qEd48oIBH9RWQklJ1Jw3blCybzUTGzZZCbo+Eq6dEoihcAG1aRpDvT2FthHBRA2awYW9n+bFOSqahI+20T+LxuwN5ZSkpiNRQCcOuCGZkYko66giABYudWf9a2kBH75wYhNykkecN+P9Z4M5GhnpOoqmDnzmrT9wP+2UrAvAUN+CTaUYGdpxNpOTRky5cCwbrl4jQtECm1M5jrF9yKyp57AcKWK8PnAj127lLxwo0c3a4DPdYvfqFBISiLx1S9YNu42Rt7heUXXnML0ck49+y0xL09H69n4aoaeoXZIb9/Jzi9isdyxgbSvN+L/77vo+cZM9t7/NRav/UqnSeFKPH57v8h/ncyuaWv46ZsA7pinQ6tr35q0UEYEHYbstGp2/2cjoxz2gq9rs1lFziVVU/LZEob3KEQ1ZxZs21b/iunpSn6FZrRaqXVqoh6sHaWTvTOBM+/+Tim2BD42G92KJeSanSh3C8A8cTJTpjY9h0XK0UJ2v7+f3lWHCI+2QN2zF0TfgpSSooSAXqNICddId1xD7HEOtMPawxbs7DDu3IM2oYQCDLg9eDPSVZxna2u4885mFLgZyT6RQ8r7vxF53yBMzm5Ye9m3P5ONSoXfPeNwC7EjYdEivj87k763BF02yauduyX5TiEk/utrQl+Z0ySnIg9PianPduH4kVCOLtmPT+JZnIIDiHzlNk48/iUOWXHkRQ4h7O5rE/nW0nQZ4EDekfVse9GKoS8Ob9eZiYUyIugQHD8mc/DdPURk7cXSXVZCKprpBX7m4/V0Ca7C7pE7MdTnvZmRAZs2KaEcU6Y0yzHroyK3jJP//YPi/aexmTiUMNty0j9fTobfAPqPPMWmoJu58WZNw6JWjUYl3CQ9XRkL6d8f1GoKtx2jh18uwTdPQwoO+vscXgMH3QvxG1X3eJrBA/AaYOLw6tXXVJZrjY23PfluYex9dgWOacdQBQcS+MwtWHUPVbL3WbQT3wdJQj9yIJEuNrh//QOrv5/EiRNdmThRybEWGVn7EVWpJXr9czjr/2nG/e1FODw6t0lZeSUJukarCe3Sh2qjjCXgY12ANrSCkwdMGON243tTX6wdWz76raVRBwUw9MxmDhzWsPb3QYydqG13eut5hDIiaNfIMvz5J2zbJuFvMOMcaAcOUr3OlQ2iokLxdOzRo+ZN2f+54agstKDTKL4o58nKonzVJqqOnMLRXVd/XvimUF2thKyoVIrzhkZDwZl8jj70OaoAP4IfmUjuL5s4XqDD5e75TBzvgbqsD9OtrK48JF5cDL/+Cqmpyr6dnZXMsn9pMN0WNGB8p7U4fz6agdK0QgypmTgGOig5YvR6xeJlaalkq21FnywrBx2jFg5g19be7Fm0h26xP5F6x9PYDeyGR6AV0r33KCvatxOLSXQ0rtbW3PrDL+w6V8qHH/ZDQqakRKJ//9qrurpJ+M4dydafzEz4YhHq+XMVT+UmoNMBfw1dmD29OTJgAXlpG/DMPETc4gP0uL/fVTasDWBtjdZCRVSEkcU7ktjl0rnOOW0vCGVE0K6RJOULK375CQLSd+L07J1gLzUq50dhIZSWyPjkHoYNG2Ds2FoveY1t3SQP1dWwd20pph8T6BMDDBx49UMY2dmwf7+iMHh6KpaLG28EwCHQEZ8Fkyg5nEDi/1agGjmMQff1xcbuL7usnd2VH2ZZhvR0qnOLyEo2ITs5UzRqNupUW7RapXyLlVU76NyagYxjuZz+aDMuqgI8napw9dVjaashI74Uj6A/kXrGKMlKrvKaVhdVoLXWKY6/f2GuNrL5vp9QRXXFcWAEfoFqHBwgK0vRhQMDlduv/xAtvkED+eWHvrid3Yvnph8wbtmBx/5DaMaOwuDuje6GJpbIvdZ06oR23mx6f/E9xbklZJbZ8md5D1xcLGqKIJ6n/wCJz0+O5liBmehFi2Du3KtO369Sweip1iR0ncyW73rgtn0bXe/shdaynXeB0dHg7Izlzz8zxfM0n2zujJ2d4gt1NUl1W4N2fiUE1ztGI6z76hwjy1agfmw6dp0al3Hx3Dn47ZMM5rqvhpxUxSwcEXHJ9c1m5e/nb5fSdcNiXHv6Y+FfDv2a+JVlMimWmL174fBhyMuj0juIMlMCTk/dg/SXxUJSSeRuOUFFbhmd/3cfXpGNNF+npMD69Riz88kKHUr8wSPs0cygar0dtrZKHovrKbFWp3Eh+A4L4dQp2H6wkozYQvqeWYacWUp6qZoIp3T08h7ljd6o8s61OfLhDkz7DuJ/Q1c8x3cHDw/ksnKCB3tRsWczhdvWsdImhqJOPfGyKiQh3YqAGGdGj1YMAr6+cO8DGpb/0J38s/EcSnUgIOEsfp/+SLpzN8JkI6qJE9qHQuLtje6+efR7/zsKCos4nlfCkiWjmTcP3C94bNVqmDxF4ovPx+LnYsbp668V652t7VWXaw4JAf9nfdmy6WaOHzXSvc/VNalNEBQE8+fjvHo106fJ/PSz4jMWEXHNXLyaBaGMCBpFU6txthRbVxYRsu8HAh8ZinpQ4/waTp5URiyCNaXoCzKUmQMHXraBlRVKJPzwpfeT7dadoOduBam86WZ9lYqyc4UU7UmlKrmaogonSrI0+N4zmvwiVyyr/w5e6fb0BPT2Fo3K3WLMyKHglw2UHE3ilFN/DulvxzrFAqchkRiyLOnXB4YObT9uCM2JXn++iq2esiIXdi6ZwJ5EV4xaS/4shKkBENJ0PQSA6MdHcHh5MLtWHiZozRcE9XLGrlco/rkH4cnpYDDQc8ceio9s51S+G/bnCjhRNYMP4oPo1w8GDfrrdrS05ETP2ai6GzBmbSA/YS822ekk/bibYJNBSQ3clh7MS6AyG3F2MOMcZCZEtZvBU6PIynfHza22PuXhoVhIfoodz90BqzB88jX6/j2U/PhXmSNfq4WRo1VUVLR/n5EaXFwwT7uRs1uMmM3Ku2jPHhg5spXlagRCGRE0mLJSmf0HJIYMaW1JFJLiqqla9AMxN3ZGPbBxlom9e2H1apDMJroZ9kCoj/IyDwhQ/ELqUS7SdpzlyKu/wXw/LL0ckB56FGt7DefThDWJQ4fQ7tpKfKYNFknl7LQfh6edmY0nehFqqhmlAcDSsZHhiCYTOxZ8T55TJ1TDHsKviw0LApUv7uRkS8ZY1v4ivZ6xstPg1tOP4eHK5TcYlKy71tbKiFlT0eokes0IJOKGQLZtGM++P07SJ347oS4llPz3Gxymj0Az+zYc0tLxe3kR6mAD3UzfURUxHim0J9XVimHm1lshPx+OHtWybt04DPbjsLaSsazIZ5I5i/DMTCXaqa3j7g4LFii1BXbuxGnXKpzmzq3XsjN4MMTGSnyZNYFBZT8StmGDUhRpzpxmsQR1NEugysaK0RMgNBJ+/10Z8R00qP18aAhlRNAg8k5msfrbPDpP6dLaogBQUS5z8t+/Eh6lx/7WxpupIyNh8yaZTseW49mlFGbOVjSUP/5Q3vwXUF0NG9bLJH2VSJ+j6zjHfHxffQCfkKt4fEwm5DV/kP3ncQ5l+eJgTGJ1+OOU+IRTaV9NtyiJyZMvkXq9sBCOHlWyv14u/aJaTY8v7sfGsa6HfUBA00XviEiS4rfaGAz5JWisLf6uVCzLylSPhcLKCsZMsiA/Joy4/yWyLs4GG3UFth/vJjojA03/3vjMGwNFRYrPUNFxSDOCdx/OV611clKsWEOGKAFcWq3E6dPO7E1wxtYM1ybzTTNgYaEMa/bqpdzHqan1WjtycpRh2KKUYrKyqwnzA86ehYQEJVeIoF78/eHee2HnTuX09urV2hI1DKGMCK7Iub3niP/Xd2RFzGZcGyiHIMuw79WNuEvZBP5zfpMqsK79Q6ZX/lq6dz6H3Y3j4dtvlTDXixQRsxm2bIEDy1IYuvU9tAOVHkvVOQRtU628ZWUUffYzp/YWk19qh41VMTuj78fKzoWoTmBpacG4cRfpV5WVcOKE8nY5e1YJXW5AHmhbJ5Gpt6XY/d+duCTvo/OoANRdQpXKf6tWKZnTXOpP2uXkbUm/N6ezaZNyXwHEGuAWTxlNA4cfJOlvI4irKwwYoHTa7Q6N5rKlFDw8FF+mpUvt2ayfRa+pCVjtWA8bNyrOH+3BT6aVUKsVq0hVVWtL0nCEMiK4LMVHkzn38mKM1RJqT7cWLW7WUEqzyrA4sIOwt+5EsrZq9PYJCVC6dgfjfI+jnzwGViyjLLuMfJULvhd9calUIOfkMGLVoxQFdKXXt0+TvGFtk1+E5WcySHrlR85kWmFjrqbM2oO8UVOYPtICf3/lw9jOrp7dp6TAmjVKr+PlpeQvp+358FxPdHtiNMu/jCHh1GlGlR9H8/sa1JKMlJgIw4YpX//1XBxZVgwBw4crDtRpafDTzxIzZzY9W3kHyXJeh9BQmDcPFi+WiKcTUfcGw5Ejl7SmCGrTXoZoQCgjgsuRmortqh+xVFdTHhhCSGdV63+MyDK2SUfpPdEDKcy30ZtXV8Oejw4yVLsd/fw5lBj0pJyUyDhnRcw/+9fRAo7trcD881J854wg8P57UevMTRI7Lw+K842kPvkjVZEx2FTEUx3Yj953DcDP/+9jXlicr4aiIti2jbP5thRllHPU6UYKPtKgUsGkSUrERWO5ihIggr+wd5C49UEXfvvNhQ/P9meI1QY8z2zHy8sI69crHtKTJ9exYEmSUgE6+C8roywrl7i8nCumTL8ecXeHu+5S6iShUkH37q0tkqAFEMqI4NL4+JCOF9mGAgbM8MPY2sl0qqrgt9/gxAmkvywDjWXP16cIS1qD5+u3seWwPRUffEmebThuN3bBcUjtXj01vpLUl7+l+xAHPB+6CdRqDIbGKSNmM+zereTTevBBDc4f34uduyXVFQPQWTZgeCkuDpYvp9g7nKMD7iB5czJ5+U74+cGMGQ2POpVlyMqUST1ZQmKuHd27Uye/g6DxaLUwbRqsWyuzZtsAdN4DuOuuC/J0NUDjk6S/02jsfmo5Vp28Cbu1R8PujxYm40A6aksdbl0aXyumObGxaX95MwSNQygjgktSdTSOMzsycXvufvSh1XCVYY5XRWUlLF4MKSlUVIDlZXKBXIqKYgOmlasJemoamgAf/L79joM6RxJDx3HDTFWtp6Ewq4oTT39Hp+7WeD54Y5P8UnJyYMUKSEuVGeJ6Eqt0C2WsG67c0ZhMmNZuIOePA+xxvYET8aF0itShjehMH3/FLaFBIlVVkfxnIvt/TMA6O4nTnSbQ62Y7oYjUhywjxyewOS0E/wCpJvnYlTAawSxLqKwtKa+GFetg9uwmWJ5kGfdBnUn/fhPblu/AfsowIm/pij4nlUo3P/SW196Ulbf3DNkrduLzxC10Htm6wyLCktexEcqIoH6MRhI+XEdJz2EM6mMNUivXqNbrMXgHkLA9D527I8FNyMhoaadl4OIFaKwtyPhwGbFHqvF94lZsy1W1hkeqywwceuJ73P0sCHmmaQP5RiPs2ytTfiSBmKQ/ielbBYH3N2hbQ1E5J5/9noQ4I9U9xtNDimPUeLDq042MjEaEmp47h+mb75FPleOaAqc6TyJycnC7TRfdEpz4ej/pv+7G6OCCyckVt+zjmKu0/OE6iKqQCLpFq4iKuqQ/KqBYR8aNU9xEjh6FffuUwKw+jU2oJUkETuhCwNgw0tYcI2PxJras2E6An5ks5y64zBhOl4hr2yNH3jeIZBc9Z1//lryzU+kzt21E0wk6HkIZEdRL1m97SM3Q0PffMW3iiyR1+1lS3t3Fvq7zuHdudZP3o7HRk/7dn5xYnYL/8/OJ6KOrU+5Ea6nBY2QknWd2R9I27RGRSkuwX7aEQTlnkTRgN21Gg0wZpaWwf3URlZtO0WOoO66m5aRWdeaUpis9aLgiIhuMnF0fz7lt1ejV4H3zIIq9ejB8eJOac3W0YQeVoAnhuIbYY8zIwZSVi6ayiLNJZrrkLkXO3ITZPJBE62hsbFRXrDqv1ysZ5Hv1UgKzmtpsSa3C94YofMdFkvPFb6SvOYL5+DYOJJoof2gUPXvVv9Pq4krKUvNxjGjefCMBN/XCzseOuJeXsi6liAFP9LzqfRanFWPrZduoBH6Cjk27U0Y++OAD3njjDTIzM4mKiuK9996jd+/e9a67aNEi5s6dW2uehYUFlZWV10LUdoupqJSkr7fidOtMnF1bP1Rj79ZKCl7+lVSfEQT190B/FUMM51Ye5PS3e/F8ah4RfZRxp4t1BEklET67/nuqIcgyrNlqjYVsSZ+uUO3uC+Hhl92mqgq2/5hG4Zpd2CcfwcZJS9aZcs4Y9WROn8gt0Q1/aeceTCHhfyspLlPj9fBcIioPYBo/nCB1y+oEsslM9bJVWKQn/Z05zMVFqWR8OdNCK2LpYo2lSyegE5w7h8FbTXmpI26dHbH1c1ScPywa9wxIklLn56qRZVyivEnPlKg6lIFP2m5OvW2i/O6xDBos1bmWp9cnU/D5UrreOxCHiYOaNczKqV8o3d+eTez/LebPpwthFJCbi9nds9GHkc0yh5/6EbuoQKL/0TTfL0HHo10pIz/99BOPPfYYH3/8MX369OHtt99mzJgxxMXF4XaJnAt2dnbExcXV/Jba6BdaWyLuoz8pcgpk5E1BrS0KyDKd4n5nq50rmf59mHAVCXzObT1D/LtrcH/kVroMc20+GS9iz04Tpl9+ZUC3PDSDxqLx8SEpWSIg4NLKgC7+BD4bl6POqMZaLqTSxoscjQtFXfswdZZtg/xDqooqOf72Boq3HcFy7BAG39cPvbUazJ5oWvoLNC8P+ehxjq5Mpjo9H2trqOzRHyl8OJ3VGppWd/Ua4+2N1tublkylc+zjHWg00PnWnqitLC6Z7RcAjQapT2+i+kA3GcqKjIScyiKnuozsbJs62XMjpoWxzTCXA4t+pc/ZBGxun6pkSjMamyX2Vx/sTfR789C/+D2n8SPr09840uMuxt/QuCg7SSUR/uw0jj32JfGednS6vfEFYmSzTG5sDq4RV861I2gftP5nbyP473//y1133cXcuXPp0qULH3/8MVZWVnz55ZeX3EaSJDw8PGomd5H/+rIUxmaQveEoEY+OborPZrNTvusIx35LwnX+FKZOk64qNbfezQ7PBVPpMiGw+QS8iPhTJtLfW8Lg8FysFszBFNOb9bE+HDwIktFQb3YqWYY9G0rIzjIRUH6CPLUr6TfcTUbfqYx6vBvWDXTXkc0yVUWVRH5wH32fGKgoItDiiUgO/99Sdt3xIcs+zGCf1VCKNM5s8buD+MDROLtrrrbgaofCKsCNjE2x7JrxPxI+2Yhx+y7ivtlzxe0kCWwcNPj29abH4LqKyPl1Bs30wjT/HtYf9aDifx8radeXLm22rGiSkyMhtythLYm7s0j/dTern9tJeUZRo/bjGu5C0LO3kvb1RtLXn2i0HDnHszjxyGdkHc5o9LaCtkm7sYxUV1dz4MABnn766Zp5KpWKkSNHsmvXrktuV1pair+/P2azmR49evDyyy8TcZlIjKqqKqouSFtXXFwMgMFgwGAwNENLms7547eUHLJZ5vi7f6Ad2hv3cNtWb68xp4Bj76ylYuwkhg21QJIMXI1IdsEO2AU7XFW7LncNcjKNnHxpGT3DSrF54Dbyq3Ss+NlEWoqB26KOY1ieqOSduGBbY7WZfa9uRHXoADbOGhJV0Tg+9TDD++nJzwcnZ2OD26y20dDrtcmXlK+lcJjYF5uZYwhxtyDhtJmcVD9uHGSFm5siQ3NmB23pZ6Cl8RsRgM9Qf07/mUb8L7vIWXWGykowlRTR6a6hlzSdxf10GPdefjgE/V2tOXFzCs7dvLF3qv3VMHQUbJBG8+OuYG5c9Ts6UzmqNWtg7NhmaYPBzQ3S0zFrNQSmb+Z4YjB2Sfvp/e7tqOxrl4mtKqnGwrb+VMXefdwpumcK8e+sQOukRx3o1+Aqs47hzthPHkjsK79g9d5c9I2t29QMmIwyZ5YeJnhSBGrLa1t0rz09Bw2VUZJlWW5hWZqF9PR0vL292blzJ/0uKNf+5JNPsmXLFvbsqft1sWvXLuLj4+nWrRtFRUW8+eabbN26lRMnTuDjU38lh4ULF/LCCy/Umb948WKsrBqf7VMgEAgEguuV8vJybr31VoqKirC7TFa/dmMZaQr9+vWrpbj079+f8PBwPvnkE1566aV6t3n66ad57LHHan4XFxfj6+vL6NGjL3sirwUGg4H169czatQotE0tWd+GkM0yJz7bRcnpDPq9Nb3WsthPtpK17TQ935uNjWPbaeulrsHeVzagyc6g+6szkSx0yDKs+98JbLetwc3JQMioQLj55pr1S7PKOPLcEjSWaiKfnkTqnnRCJ4e11aCTZqOiAmJjlbojTSky25GegfJySEsxk5dcQlFSPqWpBYR0tyX6pvqLwJ3bm07iB2vQasx0ntUXp+JkSszW5G88yAH9QNK8etPLI43Q0X44OSllD/bslik4kU6E+hRDfRKQJk+qE5J15rcTZHyxBocZo4m4tdsV78GLr4FcUcmxEypOvbuOoZ3TcXv0Ns6PLZ75cR/nft5JwP/djl/3+mtJHDsGJz7Zjuu5wzg9MovuwcVwiY/Fi6ksqOTAA1/iMLQ7EXc1rnJ3c7BndS7WP31F5OuzrmkJ7Pb0HJwfXbgS7UYZcXFxQa1Wk5WVVWt+VlYWHh4eDdqHVqule/fuJCQkXHIdCwsLLOpJ6K/VatvMRW9LsjQV2Sxz4PV1lK7fhcPMMXXao3VwIPLpaTi6XWNrVFUVZGYqpS8vw8XXoOdDQ1Fp1WitFXPtrl2Qn69lRLQZo0mDdsSIWo6KZ77dh97VkV7/nozaQoODXxso+tNCGAxw+jSc2pFHemwRgZ009J6kRsrXKKFMTk6N9mvpCM+AvT3YdwW6WgBKtFFlpXJK6jsdAQP88Y65i8Mf7+bUq6vw8zaR6D+M3g/ezoz1y8gpPUXmmjy+PXkXLqHOnDunlCGwtg5gpzqA4HEywfbFdRxmw6ZHY+9pT/y/f2J/egl9nhyCWqNoJKnbz1KaX034pLoKUs010GqJ6QcW1pPZ+/oyRn22GJsFs8HSkrA7+qMpKyfxhR9QvzKPgG51P+hCQyFp1FDyl5Zi9cE3qIeoUD30YIPuCa2blrCnbuLUP78iq6svdlGB1zSlftehnvz2a29Cl/2B1QPzrnkIe3t4DhoqX7txYNXpdMTExLBx48aaeWazmY0bN9ayflwOk8nEsWPH8LwaL0jBVWM2mtn77ApK1yu+Pi49A+qsE357DJ7R19jZOD0dPvkEWaMlIUEpYtZQLBwsaxSR9HQ48mMsk8zLsZw9A9vZ0+qYAbo/Ppw+r01DbdFuvgeaTEoKrFguk3a8kJ6nvmNs+pdIn38GP/wABQXXpNJfebkyxt/W0esvfzq0ejW9xjjRva8FOTmg3rqJP77PwzB1Bm6qXLp1ruRBlx9wsanEYFBq3VhaKunmN/4pIdvVV/wIPPsHEv3unXDwIFseW0FFsQE57RzmkjJyPviZTR+duqLvT2Q3FVa3TWVHnCsVn3xDwfItkJtLyD0jCB4ZxKnnvuPsqYo621lbw/SpZoYMldCWF5GfUKDU9WkgHj28cLtjDGdeW8LPnxdzLTM32NuDevgQ0uNK4cCBa3fgDki7UUYAHnvsMT777DO+/vprYmNjue+++ygrK6vJJTJr1qxaDq4vvvgi69atIzExkYMHD3L77bdz9uxZ5s+f31pNEAASMh6DOyOrNWBpee2VjouRZdi5E774grxiDYvWerJ2bSMynV5AVRVs+CCOQbm/kjv0RujUCcLC6qyn1qmvm4RPBdtPMGD3W3Q7+SNdelqi0amU+ub336+cnxbGWGUiPamK/71cwe4Hv+fk0liKC5tW8LCpZBzJJm5bNhUVgMkEZjM5OU3cWXg4PPEEiSPuIilwOJqTR9m4OAvzoCHg64uuJI8up36lb28zXbsqIx4ODsqpzrhM8IldiBs9P56PbVkme+Z9SubHy8l1DiX6penYrF3Ksn+foKCg9jZFmRVc6HU4crSKjH7T2LJbR86SLbBpE0gSQQ9PJLSPA8ee+YGzCQYqyuVa26FW4z13NDEP9sckq2DHDmigO6MsQ2loDNl2IbhuWULchlQoK2vw6bxaevTRst12HOb1G67pcTsa7eqzbObMmeTk5PD888+TmZlJdHQ0f/zxR024bkpKCqoLPisKCgq46667yMzMxNHRkZiYGHbu3EmXLiKlcauiUpHyww7sxw/Avbc/au1V6sQGg5JHoSkmUlmGrVsp/2MLCXFm9jlGk2qUuO22xn+wyzJs+jQe711L2BoxlVv7t3xH2x7oMsITVZ8bSaz2wb5kj9IrXiIvUEuQczSDtH98TrTaggqzgcpj8eR9Z4f3pBgCp/dAsmtgCMdVUB57loLv13JcH4I5ugcRlQfY4XUjbl5aRo2CxvrG2zmouPlxb0pKvElIGEz8KRNbjWqGzuuPVFpK0KlTBDklQ1DjcgXpnG3pOasLiZ//Sdx2SM3eScgbg+j+8k3YvfoLy14w0e8eJYGfqdrEsQc+obLPEAY91B0LCygpAVNOPtWVMlllEHz0BOqBA8HTk8Anb0J68RsOPbcUp84uOE0bSmT0BV2QTofuhtG494qCVasgMfHv0saXQZIgKloifeoNqBd9TtWX34HzUGigxfxq6dQJfncOJVsTgMe6dTB16jU5bkejXVlGAB544AHOnj1LVVUVe/bsoc8FBSA2b97MokWLan7/73//q1k3MzOTVatW0V2Un251Tv98GFNRKZH3DsR7UNMTqxUXo9jfV69u+ljtX+ky9dYaKjXWZLl3Iyiopp5dozj6awIlX/7M8YAb8LfOxb44tWkydTCsfJzQhwXQpZsGBgy4pooIgGdPb8K+fJK8IVMJCjDTc7gdA2/yJChQRsrKbPAX+NUQfHMv+n7/EGNvcWRA+i+YY0/h+sd3HNtXyfvvKzVtmiKGrS107w4zblEzaNBf+7CxgZ496ygi1WUG9j67grL0y+QEkSTkqGjyQvtjVFvgnbCFdT/mow7vTOi/bmac+Xd2fXwUgL37VXRfOBmn3atZ8lIsWVmKBWb6va7kTZnH0bAZZFQ5wfmhda0Wtwdn4ielYt66nePfHqpTigFQHEHnzqXBcb6AhQVM6ZNBz05FVBVVUbLl4DW5rqD4+ERH8//snXV4W9m1t98jli0zMyZ2HLDDjBMcZu5QO+V27kwZbvHefoVb7nTagQ4zZTJhZgY7cQyJmdmWLYul8/1xkjiOSZJlSvw+z7SxdHTOFpy9117wWxwJXIeYl49YWgYtLcNy7euJMWeMjDMyXCW9MijMbWbq3tpJzFNrUPl6nniVnQ2lp1vhP//pW8HSFfR6nB99wi71zeRNe4gZS3SsXu2ZbVNXK9KcPJvU+kNM5jzEj2yX03EuIQiEJ/rwwDNRJPzje+h+9hzCww/BsmXStna4kg79/fFdOovoND+0zdXE5XzOkjN/JTWomfLj9R4bJJeRDyD3L1fKsNoEsr/5Mp3FdX2GbGSB/sz56WqyXn8Wzc0r4MABzuaIkJKC4tGHSC3bAcC59cW0BiaR9et7mF/7CR//oYQzZ6QqngcfEsh8KINd6d+QLPuGBgAUDTX4B8mRyyHw/CHOnOzNGkF6I+4arfHxRP7308y4NRpzZaOUvDVMzJgBuZUBHNcuxfrhZ/Dpp8N27euFcWNknP4xmzmfY+fiRe+cLvf5fcgiw0m9rf9eLf1RVgZ73q4hduvL0NTkkiu3VxwOnB98xKHmNIp0Wdz3bCwrV0plp25jsZBGIVP0h4mUNRB+54JR2xzuRkQmQ8o2dFXOdqgICYFvfYuY13+D7uE78GspJWbDC8zKfZUp4Q3o9d4z/K+1bOQqOQv+323Yp8/m7LOvsulvkuAa1t4bT4bGaljw3QXc9u9bER1OHA4I05mYkSXl22TU7eaTDx3YUtJJ/tYtPMD7HPmomm3bYOtWWLQIVq+TY5k+74phoZoykdS/fJNZzywkKaSd/A9zByVk2IOQEHy//UXC7lok7ViGAVGEo0dBbjNTu/8i9sZWqKqS6tjHcZlxY2ScvnE4qPnHJ3y8Xu6VEvqm/EYMe06Q9l/rPE7ebGqCD96yEl1xFB+xU1plEhM9Opdj205OHrFSkHQzjz8urVOetvBo7VRx+IyW9HSYMt8P7ewpnp1oHNfo6GBYyya8iSCgiQ8n7TePM+WT/yEmSUV5gZnDX3mdI5818Oqr0tsbLCd/vYWCV490M0pkcgH/W5dwNvZmko69x7kXDkr5Gf2g8ZWTNVPyZpCRgfrrXwRg4aQW7ks5TWUlkJWFZu0yZuS/jbqlltptZ8nJkZLAeyglqFRob19F2l++xu0zq2lq9MwdVL6/nNw/bu35hFwOK1dK7ophCNUIgmR4Kf005GXciykoWrpuaemQX/t6YtwYGad3RJGaf20ge18bcoVAyCBlMESnSMGft+C7dBbhUzzLGbBapR2X0a7CrtCgnhAvVar0ogszELaz+Zx97TQFU+/n0SeVbicQXo3DAdv+XcZM21FCn7od9bL5PVsB36CIIpw/D8ePw/79sGMHbNwI18gFuX/e6hr43e8w/+3fOLZsl4RMxqBxopQ5iL19BnMeSGJCsh3Ve6/TXtzIK69IhvdgiFw9jZoPD3H+95sQ7V3hkPR0SL0nk6Kpd2HcsBPzsRwpWdRVgiVJeuGLTxEl1JEaJ7lyfFfOJ+tLs7g153+ZefAvbN5gp7m5n/OEhRHw4DqiIiWDwdxmRl/s+ptWRQTRsC0b4+mC3g+Iiho276S/P9x3H9g1OurXPSGFptz5TMcZW9U04wwf+g37qNyYg9EnjYiIwUtBlGwuwF5dz8zf3e/xOVQqmDkTjBermeY4g+yur0rJem5irWvh3K8/o2zaHTzw9RBPbJluHPykgcRj75Pyk5thxnRwDm/Z6KikuhoaGrAbbbQetFGUZ8XkE0Jn8lTuuVcYtKft6C+3EqUBlbKWup2NTFjXSvByp6SgNZbCYxEREBGBDLBViHTuaCKutp3SzlBeeUXg4YchLs6zU8fOi0X55y9x9ofv4PzxO0x55iasehPajBRuWiEyX2inolNHWZmB9I0b4Wtfcy//Kjwcbruty/tgt6MxthCX4Yeq7AKP8gZ1dU/1v5ERhCvf17k3zyAeP8mcl7/s0gYjKs2fU0vXUf2vz5nwl3j3S5IGwNphQeXn+uSQmAirVkGnTQUPPSSVJ4/jMuPGyDg9uXCBgLwj+PmBf2wQvjGDO53T7qTqlW1EPHwT2kE2tDpyyMlNxs9J+PIiPHXX5PxmE21xmdz2gwxUg+xvVZLTgfW1t8n84hwUsy9Vag2DiNdoRnSKVOe10/GfDTQ1iKjVoI2Yh3xOBl+4T/DEfuxB+HNfoOOjHZwTp1AZk87WBg0LKmFZyuDymUeSuHiBuC+GAWGIoiRZ0d4urfWe2lcRaYHMeP6LnPj+h8h/8Bqdog8zXv46cq2KBnswEd/9AoqGGpw5h5EdOAArVrh/kcuDUyjgnnvwTUlBaFHg/OBjJt09H3AtP2zKU3PZvb+Quv9sJvJrrpXHTn1kGmd+mE/CJxtRPXKf1wzRvLdO07YvhwUvPuHWOefNu+T1k8u5Ut40lozjEeTGnjXH6Z2JE9FrwrnoTGH+zUEsXz6408nkApO/MIP0hwZXVl1dDfKTx4iPtqNYstDj80z43p0s+83qQRsina1Win71DsnLEgi8a5Af0nXEiV9upvjPGxADgpi2wJfZf3mElG+s5ZHHFV4xRABSZgUx+f89inJ2FuHxGqKjobxcSn+4HnSnBEFy+kVHD34tC4lQMHdNAE01Vjqr2yh8YTcAzWcqOPv9t7BFxiH75telrf1gWywLAkyfTty/fkJJxm3U/uKFK5U0A6H1lRH65bsp23ERZ/ZZl16TkCjQsfRWqg6WSfFAL5F4y2TMVU1U7+ojBNQHgnBVAvxVXp9xBmbcMzJOTyorKTvWgOYLz+K3RAaDXLTF7TsI9RNgkIqjJ3bqmWfeg/Kuhz3PNAUC47wjcnXx3ZMERmpIfvaO8UnnKiZ/YxmawLXIC/MgKQl0OmZ5+yKCgFoFDz/s7RNfh8jlNM2+mfqiJNRnjiLbdAzDusnM+N5NnBLh3HdeY+r/PU5wWrLXEj4VOg3Jv/8q+362jTteeRffZ56WvAUDhF9mLvfnrd13kPCfT4j6eYxL3s/5q3Tsvngr8Rs+R5GQ4JY+SV/4BKkJuGsFla9sJ3rpBATl+FI51Ix7Rm5gTCYoPWfo8Xjz54fJ085g4U0aBus+aNpwmM4dhyE0dFDn0evBuXEz0TdleFw9420yvzqf6b9/CEHhYrJqUdGYTLJ0F99wX+QqOUyd6lFOzzjeZ0K6nHt/MYVJf/wS1Wu/yOmPShAQmfn9m/BdMpNz33mNltNliCdOeq0AJSEBAu5bzYmqKPQvvo/9nQ8GzKdSKGDGQ2kcNWdhfPNj2lv70CG5ipQUcKZnUGBNofRvn0sGVa9qau4x5QvTaTcrqfrk+KDPNc7AjBsjNyiiCJs+s6PYurH7Ey0tVOy8QPSdcwe9jnQezuHCP7ZLToxBGiO5HxWQrKzE757VgxuUFxFkwpXmeP1hN5ixffSZJEagGVzOzDjjeIogSBpvD343lrhHl2KyyBBkAjO/uxzf5XPI/+Hr1L27h/OnvGcwr1wJFZo0zm2upP1MMa4IFk2cCDWTV3Fwv5Pm93dKrYd7sZAaTlaw9/fHqa2Vclc/s91MW14N7NwJx46R/9YpCt494/HY1VoZIQ+toea9/YiG6yD2N8oZN0ZuUHJywLphK0pjW7fHaz89SplPBnNWBw7q/DaLk20bbVhtAiqtbFDGiNMhYtq4i/BHPGjiMcLCQ+2nLpLz5eeRnz0Dc+aM6FhudEwmKe/o3DkocC8VYMgpXJ+PUW8Dsxm7bWi1MQRBip5ptZf+djqYmdJGeJhI4Rkjha8cHHTqyGXyCwQahAjaVOFSme/xgb0M5eXQ0q4gO/VebEdPSd2dy8t7HOcXpMDv6A52vNeEXA5yu4V6ZYxUxZKXhyZUR90b2zE2GT0e/7S7Umjyiafijb0en2Mc1xg3Rm5AWlrg1MtniK45ieDbtbiLnUaqN54h+p75VyYqTxBF+PQzGa11FmzhMcjuu5fBnFAmF1j478eIWpfl3gsvXoTTp7s/Zrd7UeKyf8pONnH0f3ehEzuQhQQNS4favhjVYpAtLdDYKPUZGgKRquIz7fzzx1X87nfw0ktw5ox3In2XK176UjB1FafVTtumQxx89F/kPH+Q0/+3m7KywY/PZeRyrOvuoGDeE+j94wgqPMqZPW1eOXVWFtz2dCTZM57ibMhyST55AAGVtDR44AHwN9Wj75BJx5871+M4bUo0WV+cyeTiz6mtEQlICKSeSCkSVFVF0oIoVMmxnPvrbo/Hr1RCzJOrqd18Bmd943jV/hAybozcgFzYW8OEC5LqokzXJY9d+elJGlQxRM2MRt9PL62BaG8HH6WN+Ooj6DMXgxe6JGvD/dxTbc3Lg/fek4SPLmOxwAcfYLYNrSCZKMLBg/Dex0ro6CBocrTkFRmBJNfmZvj8XQNFO8uG/dqukrOjgQvPPE/lt35P47d/hf33f5IsBi8ZJpWHK8k48gozTr/M4sBzPPKgwyvRMofNyYafHmfPD7ZS+NE5j21cmUrB3H8/xdRHM3HsO4hx2wF2/PHssBokajXc9q1Esv72FM033U/hp3leS2+aOEFkTv7rFOojabn3y5JU+kCvmQg3fSuD3OhVOGUKqVKmF3eNfOVyZia3stgvm5ZWgdr05bSuuh+nQgkXLpDx3FpMR7KpOdVHIx4XmLo8lPqYGeT+cRvndjWM6wgNEePGyA3ItJXhVIdlMWF5LKpQfwBEm52qT44TedcCtm4Fu8nm8WIQEACK3Gzi0n3Jum+iN4feK8ZrvbA5OTg/+JCGehFiY7sOeuMNmmqs7N4/tJnxVitYDVamnHuX9uh0Qr79iLRFvExNjRQvGEKaGkW2vFjJrq9/TOgHzzN5YeCQXm8wmE+eo7JOSUsLiBlTkD/9lNSK1kvGW7KmmsQEkalBVaxo/Rj583+TjNVBGjtih4GwunOEVpxGu/ljOjfu8fycgkBkjBxthFQJknJ+Axv+WTXsiuIJiQL3/ngis7893yv9qNoqOzjz641MfmIWM6s+I7fEBzIzXXrthIkCi5+ZScvdX5LCs0VFPQ9SqxFuuZnZbTu47SYjZjOcNmewI+6LiLV1BKaEELRuHhf/uhmnw7PvpqYGGjOW0nCqEvk7b0hevHG8zni90g1IQb5IiukcMU89ymUpzKJPzmJGgzNmAjUFoNizAx662aPztzQ6EA4fIvbnK9FNGFpvQEsLnDwJq2c0SXkpLS3YDp8g/6yIb2ok4SoVdHQgvvEmVacb2ONcyizP3pbLCIhY3/+U5AwN9atvRu5/yRNjs8HLLyNeuEjBF/6XYAVe6flzLZa6Vsp+8THagiq0QMKztyALDvT+hbxEzLfvRbtjAyFrZ0vCGl4mflEC1ghQxUVIqqFhYYMqDb+MPMifFd+egmx3nfTdntsHzia48073ldcEAWHRQiYtXEByWS2txy4QV7CPguO3ERDgf1mBfVgQBEhL9859qw3W0pxdSUi8L5NuTSHn9fXUTn+UKBe/5tRUEMVISP0yFBf3flB6Opw5w7S67fg/cSdvvw02WySR6SvJBDK+uoQjj/yD/PfPMvlh1wyhq4mNhQzjSawOC+ZGC1RWDs2Ne4MzbozcgFTvyGNykr90l13afcauTEeMjOKjAwKRtWeQCQWAZ6t2/gfniIiSoZsz+PBMf1itUiRmlnAKNJ2wZAnt8iBOHlXSLJvEylnBIIpYTuVyYmMLdqOIYXaCW6kboig1LfP3d/01J/+whyBLHek/e5pJvpcMkdJSxF//D5155XwS+VUO/VvL//2fe+/XVQw2NW2tIn5aEJKTiL7d6yofXiU2Fnjy9qELY6WloUpL8/ppZTJg/lyYN0cq2dbrpf/q67s8cu4iCKiToolMiiYSmOBwwBhuc6T2VRD+tXuo/uvLzPnDvdhLt7D7N0dZ/fP5tLW5lkYlCEhVaJMnd3tcFKF850Uip0ehuflmeP55LJpMFPJEbDaBrXs1pEwGnU5F/JdWU/rCVpLWpeMT5F7/B0GA+T9cygFBSee27TjKKpHPGt331FhkPExzg9HZCeLJU4Svm9lt8teG+FBsjMKnvY6JFzfhUHmWcGoxOencdpDIexcNqSy6KML69SCczSH69EaIiKC5GT7+TSGOmnqqZ91B4J3LQBC40BBIfT2Y1f5EzY51adMqimBos5OX6+zuKh8gXiw6RTRKB+m/fAiZzgcBKYGk5Rv/TfH2Yo6WRrCxYR6PPOIVbaYe1Oc2kvPNlwhP8WPKF+eS9r0hXOS9xVhXqhQEKUE7MlLKvvTUEOmN66Dh4tSVEdRkrKTyX5tJ+ubNzNTv5p0/1rJvl92lqJbZ6KTxaE+viCBA8YenqXx9txQbXr6ctIsbeW7aTm5ZY0erlRprgqSoqokNJedv+xDLyt2WIREEWPT9BTjW3oIhv9K9F4/jEuPGyA3GxSNNxFCNbsG0Hs+tXGxhUu6HpKXYkfl6luFX+FkBfmorEavdd4e6w8GD0Lj3POkF61EpRYiMJCTQwayW7dSkLSdpkgZBpaS2wkbFPzagNHcQ+sgaJk93TcRt33YLrW9vZss2mWR/iCIcPjxgb3dBJjDjB6sImHCpM7EgQGIiKqWTVosPF32zSF4cw+LFg/wA+sDaZiRsxVSm/s8D+N61moDEoKG50DBx+rRkdH7wAbz1FrzzzkiPaBx3kclg+lfmkFsfhuHwWUqjFjAh5yP8dn9GRcnANcRVBQaKf/N+r+W9QfevQn/grJTY4ecH7e0ojx9idlQV3/qWpLvX3i4dm/G1pVgPHKPg5+9SWWLz6H0s+95sZMuW9JKoNs5gGTdGbjAat53Gb86kXvU6KossdEZPIDrND/9I315e3T+iU6Rp/QFCb1/guiqph8yZZiaus4AAfxGlnwb8/anbcJzqegW3/Gwms2ZJHvP9v9iF78VsIhM0zLwrgdTUgc99YIsBw99fpaJCxGCQGv2xZQucOiXtwNzBaqXzd3/n1HktB2Y8Q8G8J3j2OWHIHAFxixKY+swKqfJorO6qzWbEAwdp2nee5nM15J4wUfP5KRQ7t7IyKlc6ZryiYUyRkipgXH0n5buKiRGqyVKcI7LxHOc+7SUp9RqCE/0pCFuMc9OWHt97xqJgCgPn0v7hNkk6/nKZVHGxlPuSdinEKop0HMlFrXBQX26m9sTAFT29IZOB3+KsQUkVjNM748bIDYRB74CcHKJumdHr8xfr/UlRVyEsWQxr1rh9/o5aAypfFUn3zhzsUAektFaDQ+1D1v0T0S2bhb3dSOlr+wh9ZA2h4TJiYqDhTBVpO56nwzeS6IwABH+/ASNHhz5vwfDXV/DtqONsexJyh5XAbe9LYk0pKe4NUhRp+t0rnPvkInsX/oSvfbqaH/0pbDz3bQA6OuDwn46S98sPidn0IksL/s3ExkOEFx+h9fXPpYN2774hpPWvFwwGUKjl5DimYD1xlmhtG7NnifiW5g4kO0JgIFTHz8fYZpU2BFeh0YDP2iXU5TZBayt86UtSgvK1ya4yGZFfuhXTLMkl2ZZd1u81OxuNdNa2932Al3cToghFG/IwNd24Sq/jxsgNRMmWQvxDVfhNS+r1+aozjUQLtZJv010PAOAf48eiV55EoR36Hu45+/VkOU4hW3UTyrU3kf/CXjpD4pl+b5fBYN97kFzVdGbcEoXvhJgBz3k+x07bhv1oTS0EBEBAZiIzjQdQV1yqcXTFrXIVlW/vp/j5zZxf+Qw//U8yWh+hq6PnOH2iC1aROCOY+ctUmLPmUrzsi1QkL6NJHsFhndQOoGHaynFp/TGETgeJE1WIcgUGpw+WxDR80uJYFlWIWuhfNE4mg+BwBfXT18Lu3dQfKGT//+y/4iTJnKPmiM9NOLduB19feOopSTjlmlCKQimw9Fc3obh1Ddaicmz9RGrO/Hkvxf/eOdi37TKCAJWfnKBqY/awXXO0MW6M3EC07j6N/9Le9Rva2kCVn0PA3PRR74JsbQVx/wEil6ZJiasFjTTvPMPkZ1dfiUy0ZpdT8FkBKakCMf91H0G395+k0dIChcUKlHYjoXEadFmpVLT5M/3OBKLilVJyojuynaJITb4e6w9/zlOvLhmzEZORQJDLiHlqDTWz78R5+BiJH/+R1ILPUabEMfdJqaIiPHyEBzmO28ycI2fa99aQN/k+9FYtJCYirFmNX2PJgK8NDYVav4kQF0fgxZOoju1nx7tNiKIkbd8Sn0VDuwbL3iPS/PXII72G8mQyWPid+UTdOovKsu5ZrKKzK5s25JZ5mE6elyabYcJv2Uza954aEhXiscC4MXIDEblyKnG3T+/1uaILTtLMOajmZA3voDwgZ28rk23ZaNctA0AdqCXyK3cQNbWr/03+myewKPyYsG6CNFv1o19hs0kJkpaDx5l4+DXS//t+lA/di0K0EXFqE/I1K6XJzZ0OxoLA3P+9ncX/Ncs95dgxiChKxpxX0zhiYlB0tJDQdAqdqYGYubHc+rV4MqaOT1ljmWnTYNk3JlOw+GlJPGzWLJfCn6Ghl7TG1q5FUVFM+tII7Ju2cuiQFK3LmCJjh3wtpW8cgNJSSUK+j06fggBznppCZEzXDkF0ODn42ItUn2kAIHlWMJW6Sei3HvHK+3aF+NXptNWasRYOs9LdKGH8zr6BSLs/E11U7/WkdYeKpV527uZFDDMOB7Su30fY0gwpNgzoovxIv29qt+OE5ctJjuwk5MFVA55z82awZZ9n4mf/hy4zFUVaCqW1Guaa9kpy+bNmDU0d7mjDjR1ZW5uk2P7JJ/CnP0FJifcruc0OFdW6iaQsjGTSHH+UcZHuGYTjjEoyMmDaTWFw993SDT1Arb0oSsZIUxNUm4IpLJKj33mCFcZNZG+oYP97NZw+JVLTrqNDGQxvvokr0rVX5/ALchmBk6I4/9JhRFGK8giLF9G658ylBkRDT1iUgvaU6TRsPjks1xttjBsjY5RB9ubqhsMBthPZBCyeNqTaIN7g4tFmIppyiXhgWZ/HOJ3Q/PFeIldORYjsP1s0Oxtqd+Qy6cC/8bO1EPzASgCqT9WR2nIcbrttbGtguEJnp1QrffSoS4frWxxs+EcF2X/bT/HhembOlOw1b5N4RyZZ319D0M+fgbvu6lP1svKdA7S+uxWxtGy8ymaMEBiItOK7oITb2gr79knVuzs224ieE4d4oQi5QuQe1QZKf/MuE2x51NaC02CUfgMVFW6PKe3JBfiU5nL+iJS4mjQ/klJHAhw75va5PEEQIPCmmbSfKJQyfm8wRvfKM06f7N/vvXNVXTQR2lJI8Ios7510iKh9dy9BS6YhhPStj31hXy1BDQXEPrZiwPNlZgITJ6LrqEWWORXZxAl0djgJPPA5gWvmXr+yz6KIWFpG+R8/wvGHS43pZg5QBZWbi/WVN6h/9rck7v4PMkFk0rIIli4dmiHKfdSwevWAydSVuy+S95+jlP3iNeyvvQUNDS5fo1Nv75YrMM7oIzhYug1FEQLDlATevxpHfALNdXYiLBUETY2lc9NebH7B5Mx4EoKCJGPEzdwLVXQoccsnUPj6UWw2qSz4rP8iyj88Tlt9VxdEu00cst9M6pxgShwJOE5lD8n5RzPjxsgYxGKRNrGXxXwG2x++flcuvsmRCOFhgx/cEOKwOdFqIf7RJX0eI4pQ9+YOglfPRhY0cEVQUxMotm0iNFxGwuu/gsRErB0WEmaFoV07RKvsKMDcYuTEH/djOJqLXHBKnocBQiCtynBOvF+KUW9j2pfmkPjYEm6+eeQdR5MeymT+/7udpL8/h+Kpx9zKbi3YUcnmh97gs1eaOHVKCj+NM/q4LBIYHAxERuL7259jaDRiUvgTK6/BrDczxXoagzJIqqbx8fEo+TT+oYXE1Z/k6B4Tu3aB3j+OnOpQhNOXSopFkZNffZlzn5d57b1dTWwsNMbPpHXnjZfIOm6MjEHy8qRu2pWVSPX0vXWz7Ite4p+2sir8l2R5bXxDhVwpY94f7sE3JrDPY0SnSPjSSSQ/7prEafZxK3NCikl66ccog/3Az4+gaC3Tfnan+83OxhDNbXI6i2sJSw+WZnoXJMwDJ4SR8OB8Mh+dSuBD61iyVBgVUb2gm2YimzXDvQZCl9CW5eNbX0rs5y+gPboHmXNgRVBvYtWbEKuq6ShrHtbrjjUiI2HiRMnpARA5L5Gam5+msbCJ+YuVJEV0kln4Pkq5E1HnB08+Ke3a3ESIiyV5YRRlH50kWp+P/4a3KI9bhPz4EWnTZzQStyiB4vdOdG0GvYggQNjidBprrHDkSN/NAa9DRsFUMo67nDsn/X9VmR02bZIsE1cQRUlJ9BoW/P4uUu4feqGyPvHWDsBsRiYXyHh8NurAgcuTHQ5o/vwwkemByLN6yuNfz8SkaJj92jcJ/eKduBpnEWQCsQ8sRLjrTqnL7HWQShMxJ4FZv7iVmb+4jYylYfjbhtcoOP7LLeT88B0KfvfZeL7LACxZ0mWMAEz4xhrq6gRslbXERtiJ8WllUcA5qqqQPCNRUR5dJ/SOhUwzHaOaGCYJ+VQ1aXAqlPDii1BVRcwds0ijkK0fdgyJ82Ka/Dx1zUrEbdsZUBHuOmLcGBmD2GxS3pdw6KBUU+mqMXLmTA9Lu7HWTk0NI1d+WlY2YL8Xl7DbaX1vm1uJ78XZHcRWHib0kTUjH2sYAXQRvsgS492Tjff1HfUy8+V7SyndW05lhYjVCqKx7zBmyJLJ6JbNgqwsmDJlWHOE7CYb/n4ibVWddOZX0LJleBIlAdqrOzj1P1sQHWPHAIqN7V6hH53qQ8fyO7hQ4ETR1kStNZRM/T5iIt3sgnctEyYwIdOH+j3nCWirYNq5t3A0tEhhn+ZmCA4m5aZEHCdOc/784C7VGzErJ2FBQ309NJXfOIqs48bIGGTZMohUNrNMcUB6wAVjxNpigO3bu+2+RBFO/ml/v0qEQ0VrK5haTFJtqAsZ9f0iinR+sInjO/Ru6bXVvbuHwFmpyBLiBnf9QTLIlJ9xrqFu0ynqf/sqyhefR3ZgHxe//yLGDz6XDPdRhChXoLtnDS0zV2HWBFL9xq5h2wmr/dW0ZxeT/6990gPD4JXprBv8puPqsGBNtUitLZQmgxaZ3QaCQEu9HVnu2UsxbA8RBHxWLmCJ5gRGdSBpQiHZ/pfCvpd+Q+pFs1nmd4rNG51e75l39JSSC9Mf4FyRFkvzjVNVM26MjEHMZvATDKhSE6SMrgGMEVGEvD9vk154Ve/s3E8uIJw7OyLe4d27RGwfb5CycAeZm2E5cJy8t89g1+jcymFIf2wOCV8cWIdkKDEYeo2cjTMI0tclMfu7S4l8bDV5jjSq8jooWF+IuP4z9/KrruHieSvFOQaam3G7Bf21tfhOJ3zy10pqtp1j3ncWEvLLb3M0/n6a958flsRFtZ+K1B/eR8P6w7RuOgw5OUN6vdrcZk4+8XdsLV7wgl4iOkZg1gwniCLNmhg0MydRZo6ArVth5yCk3K1WyM0lNbgFUeuDvLOD7FwlHRlzJc8IwMSJREZChuICW7dKD3lrHp02DUyaIPIy7r2hugOPGyNjEJMJnHEJUlva1asHLMksL7KR05kqhSJCJZXS9iYr9f/ZhOB0DLsxUlMDzdtP4TyfL41pEJ4Rx8US8v8ihWfUoe4Jk4VPi8QvPmjgA4cIoxHeeGPwjqGxgMMxfMUBAStmIl+5HCZOJGlWCMoff499s7/L6cwn3e4vdDU1n52g8Iev8u6/9Jw65friY6xqwf7R+q6FDLBX1hK7/T9Ytuzmk5dbMFlkPPizibRlLnUrZFh7rAKnzeF6qPYq4tJ8CJ6dQvEL26nZdnZI+w5GTg7BEpNCxZv7vHrejAenEfjEnViLKlDLHTSVGjA0W7BV1Xv+g1OpYPVqDHYNPmE6Ch2pZFVvZKtzdVcYTyZDmDWTm/xPUFgoSS2cPeud9+TnB7fcAq3BKRinzvXOSccA48bIGMRsBn9RL8U6EhO7Swn2wv4jSkxGEXtYlJRlLopUvLkPrVWPTBxeY0QUYedmK37t1VJ4SKUaVL5GLVHog5Mw+EagDR87Kqkmk2SINNY5PM2z8xpXohdDoDRZVwdbt4js2dCBYPOiUp+L+AUrWbxSzTPPSHZ4t/XJbnd9EbdamWTNYXp8M19T/4c5yU2ueeFEkUO/PUDD3jz4+GPJKnM6keecJjXKwKK5Nr6Z8DlLFov4+bkngOywOSn402YK/7QJPv/c9RdeRq0mLVODzQYXt5dRfGYIykMuIQgQ9uBNNO/ORmz0bihq+hOZGLIW0rbtGGemPc7+omjsBjODKncJD8f/6QcIDJFTEjGfkJYiGk6UU5m2sutHNGMGzpIyEv1b2L0bLlzwzvsBKX1p8mSwxvTe1PR6ZNwYGYOYTBDcViJlcw3QubSqSpLqDmoppj0iVVI9tNnISHciijA5UzGsSudFRVBSpaItMBGjXwTccUfXkx5szaJDLKhqy4h49mGCl04d+AWjAFGUdlKtVZ0klu8bUWOkrAyOf1AGr7/ebed+LSaTe7ktNhvs/PURTn7pX/g///9YxEFKczvZ91YlJ17PQ+wY3li4TAYJCd3t3tacCpwv/Ms1tU6VivAff4monz2N/KZlUFCAS8lWFgtxUwMpbQtCrK5B3LUbQ52BY5/VUeGIoT5xruQqPHPG7fckVwhM+tJCGredpuNgDtTWuncClYqyrDvJm3gndhTU7sh1ewzukLEklPKATBrf301NjXfPPffPD9Hp1OJsaePM5EexBYVDff2gzilLSSL9h3eSMCeSBnsgy61b2bpD3mXQ+vmhzUojsfYI0TUnKS72IHzXD7fcMuA+87pi3BgZg5jNENBcAsnJAx5bXg4Bfk4iDMW0BF7adqlUNKhi6fQNJ/L7jw3rYhgcDOnpkCU/h3nCFKlRBUgxi0uysiaT6x7WyvWnaAmewIzlAUya5TtEo/YuggCTo1qYmf0K4XHqkRF5FUUq9pZw7rlXyTj+muQbjo/v9VCDAd55x722MEolRETLCbA2kvrlFRQY4yl/7q/oPnqN6ekmBL/em5gNJ/UnK9FXdsC778KePQOvJCoVxMTA9OmwaJFruU4aDUlPLGVf5rc5kvYETRWdaA5ux19fSWe1nj1nAml49DmpQsndlUwQiIyRE5uuIz8fbAddk/O/mrQ0uOPnWZStepq2glqvtpm4lsZGMM1dRt5nF6k6UCpZwl4iONYH+coVpLcdxab0oeOuxzwKXV2LMG0qa783lcL4NUQVHSTo5Hbyjuglu72hAZnRwDz5CZZEXsBi8UiFvk98fKQenzcK48bIGMRkFPFrKnHJp7twIQQYa5kyyUHEzC5hq4ajJWinJCMLD+3n1d4nJARaKjuZqChh4l1Tup7YvBmMRkwmyePsUuTGbqd+y2kib5s92qtNuyFW11D7P68wIaSFm55O9pq2WlGR60ZcR5OFvDdP4ddSjl+IClZdlcjrcFwpt9br4dVXpbVSLnMvBj/1i3NI/+VDhN8+j4mrEvCfmkDG7x5HMXcENW2uIv0rS/H7zY/gBz+A5cs9Kll2OhnwQz91SvJibL+QSOOCO7GvvZ32JbciBocQe2E3n75jwpyW6VnJdEYGiX/4Bu0p0ylen0vOQfcTREND4ZFnw3Gsu43ii0MXs/X3B32rk6aAFAI2vY2362Kj7ppHRFMukToDFqUOJk3yynlDEv1ImSAgNDWwyLmfwxub+egjJKXfiAgEAdJjOrjvPq/aVzcc48bIWKSxEZVodUk1024HoaQY7eRk/AIvTXaiSOfZYkLnDH+HXqMRFBfy0KVFIwRfSh49fx5yc7HYZLz5puvnqtuTj96sZsrtA3uIRg0GAw1vbMHS0knsBC2q+MhBn9LphG3bpI9RQHSpN4tfmIasr8whLsqObs0CyTNisyEeO47+jy9jMCtoaZEMEVNlE1l1Wz2qRAmbLyWM+oTrmP7HR9Gm9e59GSkGmzx88VQ7+/7nQL99zWbO7OpmbzCAxl/Fgm/PYtlH32TKz+9hhiqXvXtEj/MtBR8tk354BzvCHubY20X9Rdv6RKOB+x9VERg8dEuCvz/cc78cX0szNqMdqqu9ev7U+WG0BSSwxOckzc2SjXjoG+/QlN84uBMLAtq71tEmD8F86jz+xWeorb0Utly7Vor/GQxMngyzZ/d8ubHVgrFWP7gx3ACMGyNjEFVNGUJSoks7qZYWCNMX4TO1y/DorGzB3NhB/OKEIRxl71RXQ1JnLuqZl/I7DAbYtAm7HfbsFaip6S5s1B/lH53Af8Us1JqxI1gm+urIrgghclYsykmpgxZbM5ngrbck5ejJce1SVuxAiahOJ5w4QfCOD0h6bDHKJQto+PQQhV//K8d+vpmTzMI3VEvdsXJSDr3BnOP/INKnfVCVKACC6jqT1xdFjG9/grhrN+//9BzHj/deYaNWw4MPSgv+1UaLIBOIWJrO7GcXsWbt4H4HFRVS9UVNeJbHDgdBcE20tLPB83LT6Ik64n7yOG3KMCmnwwuhlMvo9SDMm0fj5hO0NtoRBJCplZR/lj3oc0/2KaVOGU+sfzuRcsm4qa5GmoPvv1+yap3OK0bn1Zz++yFK/7190GO43hk3RsYgmroyZKmueQOaq81E2KsQJnQtJDUHiiE+Hl2wG0kAXqKuUE+0s1JKFQcwmRCTUyhtC6K1QzKuXDFGWvLrMRbVkP5g1tANdggo2lWOT3keCd+5V9pVDYK2NnjpJWg9VUJ063miPnuBqtw2qcKqL+rqaP/dCxT8cRNl5QKym5aDSoXB6UPtRQOW0BiW/NcMqQo8I5ygzkqiJ/gS+MgtN6RKLTZb3x1abTZi1mUy9f5J3O+3hVRNVZ9pHyEhcM89fctGCILnH68gwPz58PjjoPMTyB3aPFQK/7J5UK+fMk+H+suPSwlkbnRYHgiFAs5bUul0atEd2QFnzxJ96wwMB7NxWAeXWeqcMo2qSSu5IEtncmQL8fFX6ar5+koGSR8JN2JaOrLii141vK5HbgCFg+uPoAQ/NFNc26UazpWiDA+GwMArj7WeKsEva/hDNIgixuO5RE1M7PJbh4UhNDcRcPtSKg9NYOJE13ZnZr2FgNuWEBA1ttLNm/ecJezuJSjDAgd9rkB/J7PbdsKJrZgU/pxSQPrX5/e7qjnDIzlXE4KstZGZ31h8JSs14fZMmmsspK2MQ6mSXh+eoCXoX0+h6NQjhIzi5OBL7oi2dtnVP/NBI4pQ8f5RzLWtpH33tp6fq0pF+JrpwHRpoWlqgn6cPxMm0OvO2VskJMBXvgIffigli4YNURPu9KcWUnfhDBdOdRCSGEykB5HGWct0MPvxfiu43CUgAB6adZHzex3ozh+DpYuIWz6N0r8pKN95keSb0z0+d3ExnI9ahbyhjrAwC48+CsePX3VAP5OWOjEKk6iB0lLpRzBOr4x7RsYgc3++Dl2SazONtbAU+cQuw0O0OzDllxK5YPjzLMSz5xDO5qCbd1XialsbYl0928vTmLnEl/vuwyVJ9+h58cz4ryVDN9ghYu6vbyXtyQWDP5HRSONvXyHgrecpDpyJ0aYgIERB+Oqsfl8mk8Hc39xByjfWoprflUgqV8qY9Y25+E+K6Xa8Mj4KYZLnk/hwYKjv5OLX/8zBH26kcIf3yhnyzjk4/Wk5rbvPIH66vn+VM4UCV1bloa5c8/OTPCRDmdDtkyq9iYKXD/LJK60e6RQJApJlljBwqNjUYqKlyDUp/7gVE0icHyVVXbe1IZMLBCydTt3m0+4P8irmzYOEJBl5k+/DERiKSiUVB7iCn79AXWC6VA4+Tp+MGyPXOfN+voa0ryy78nf96WqcyIme6eGs6KmQUGUlzs1bCckIJ3TxVVnuBQU0aBOobtGycOGgleFHPYJMQJAP8rZra8Pymz/S8MJHiCYLcV++GZ8v3EvUN++RsgQHQOGnJfy2uT2yN0esWeIgsYpKSn2nUKZI5cN94eze7R211/TJcuSPP8qOWT+iPHg6BZuLh01FdjDI5VIEZKi4HIoKrMol6cAbVBUNoXQrcPGtY+T+31bXDhYE0n54F5qUGCmOCSTdlYU1v5iOGs+l6AVBkkQSfH0wLFh95TFX8PODav9JUFg43pm5H8aNkescuUqOKqDL1VB/uBj1pGRkcg8WHlGELVvcD31arfDXvyK3GJn5/ZUo/LrGI+YXcKg5ncWLB9RvGzM4na7pYXlK/YkKTr9TgN3sQJ+cxdy1QSz7ajrhS90oZRyt+R+i6LYlERipwblqDapp6WgCNRw4AB98cFUI327n4kVJ/M+dU8vlcNttsHyNiuwPL1L+98957996b0YWxiSXS7wjQuxoza2UH6sb0uul3jcd58Vi6i+6thESVErSfvHQlb8DEwNRpCRQun5w/XeCgqQ0L4fWvVibnx/UKuMl2X4vVxBdT4wbIzcYIbOTSbjfw34HhYXYzxdw6ICb1v2GDXDuHKII5o6rVunOThpOVlDjn86cOZ4NaVSh12OxwKefDu1aHzQjCUdAMK2ps1HefjMaDW41CBzNOPQGqr/+Pzj//g/JeriMydTnrlImkxaJL38Zvvtd+OlPpb8vGyNnXzpG5e/e5uMXGnjjDfcaugoCLFooMnFeMMlLYplf+wn1pUavKm2OOS79uCfeMYmUFKjPdlP59RKuGoY+UQH4ZyZx8cNsl8+tCNTB7bdfuUj42hm07j7D6Y/ctEivYfp0SffOHXQ6cApyzPETx0M1/TCewHqDEbvQw3JehwN27KCsRESfYQb6Txx1OqX/FO0tV/pm1NYJiLVWYuIunTL/ArlNkSz8UsDYbxZXW4vhYDZvNK4jJGRom9/ZrCLyO2/DLz2e5DUDJMSZTK4l4YwSzpboOGFfy8KF05icrAYkL1Pbjmz8ju9CvrgXIYdrkMulZMbLREwJo7zUib++ioqiQF4pVTFpkmSwXH1cnwgCGV+YCcyUFjKrFcaQyN5QIdx+G3GIKBpq6OjArbYSlqYODj/zPpl/foLg8IFvloS7ZnDytzvoNCxG6yO4ZnyHhwNgszipKWhHbGpB/8+3EW/5HoLWMzesILifhCyXSwU3HTHp+JzdAStXjl7P5AhyneynxhlyTp+mvbSZqiqQmwduqFZTI2Wgs307JCRgMdhYr74fdUDXJFC2JR999CQyMz0ck7uxEIul+9/eSgDo7KT1hffYuFNDQwNMnOid0/aFb5Q/83++mmn3p3cJ2V2D6LikhFY3tC50b5M1XWD+t2dz+rz6iiOkvR1ePZJO1bqnYcUKAKoKOnt8nX0RumAisQ8tZvl3ZvClr6v47nfhvvtcNESuRRAk4ZBxpFX2nnuImhTodn8rdYiOMJ2J/f/O7/c2bLio5/yftxOyII1QnYUDb5Ry7Jh711KqZSRm+CAgIjgdWPVuNFnyEn5+kg4M7e1w8uSg++Zcj4wbI+O4hF2j42yZP+3+scjMA4selZTA+bMOWLgQe1sHxbZYWvwSUUeHAFJVT92JSqbel+5xiMG2c5977vKdO7tEp9rbIT/fswtfjcOB4533aS7R0y76IQhDb4xcpsfmShShuRnR0EnxL96EnJzeqxUMBu929PIiggBTp0oiYZdtzZAQSJoRRGBaVxOfyl//h31PvkbFiYEndblccq9fLhvX6a6fsNaII5dLUvruIghMfHAG2rxTnDzZ92EdNg3tu45Tmd1MeVAW7XtP03rR/a6/iXdmEbRSqh4zNXsu2uYpfn4gHNgvfV6bNvXcGI0zboyM4xqNfskEyjsomvkApuCBg6alpVBwUY5Vb6L0ooPchNuwKzRXklQFhZwZbz1H6jwPe+PU1FD6zhEc9u7bqj5luYuK6Dx4hoMHwW4TYcMGqoq9MCHs3Yu8rhqbDSJS/ZgyRXLJDjt2O3z0EVy8SOmPXqQzt1TqSHjtqltaKuXwjFAzH4sFSs8bOfZBOXWVfXu2lMruDohFi6QEwsuUz72f/NmP8cmhCA4dkmyr+nrvObvGcQMPLTvVnCxmR1Zy8LPmy4UvPfANVlMXkEZcwyliJgcS2phPyPZ3PLre1O+vQ50UjblleI0Ru/1SEmvcHAzGSzuI8R9qD8aNkXFcIkqswe7jx4ylfiy9qf8Yr80mJQlarVB9uJyQMAF9cBJh4UK3XAqtv9KzclJRpOXNTdRUOqRwRNfDbNvWy/EWC7ZPPufcWZHaWmjdk40hu4hjx3u/tlvzxOLFNLYpKBTSWXGHH7ff7t5b8QomkyQDf+EC7RGplNep8fEVujoiAzidiHv2Yn7pDarVyZw+3adg5KCwWKC90YLlxFmcLW09ni989zRl3/gDyvZmIuNcr+OOiupuPz347QieeVbGf/2XpPdgN1o5/t0PeOe/89m/x9Hn4jbOKMLXl+D5acxTnWbTx2Y6O6WO5Fej00F10FQceQXMia4iPMSB2NzqUYmsTKVg2v/cP+z5aWfOSFW9B3L8KZ6wTnpwvMS3B+PGyDgu4Sivoswaw4QJktu8tETsU3OkslIq09VqoSOnBGO7neAZiTzxhHfytuzHT1O0TyqRE61du+uzZ6HlRHGP48UdOyk8rsdohOLTeuyfbSI3F1TqnoMxmS4lvLtokVhOnCWnPIj47z2AX0r48OuktLXBK6/QmV9BsT0BXUIoi158jOiv3t6t/7gt+zwn/3KAI0cE3j03haCgK+KrXsV6sZzTD/2Bj/5Sxf8+H8jevd1VsNPvm0rkcw8z40szvHpdQSZgDo7GL1SNUubAaBxbm8/OzlEbORs67HaYOpVZimyCd7zPa6/17MXo4wMtwanYOiwIWZmkL41ApRQRjZ7lffjGBBI6b3A9lvpDdIrYTN21D6ZOlTZoDgcELJ4GaWnjxkgvjBsj47hEy7lqjMGxREdLu9/D75RJ5n4vREdLlQphAVYmKwqosESSsTjEO+ELUeTsMRMGkxybQnvFGLHZ4NDnLUTk7+2+CNlsZFeG0NQEjRZ/AsuzKc1uw2SR4dNLQdDRo9B0oeVS9u3AYyl48wSWzDlMnyEMbQlNX5hMFBQpOHkSdJkpyGSgDNLhu2h6N1eCMmsyjmUraUvI5JGv6K62U7yKOimatimLYM0avvY1WLas+8ei8lUy6XbvS2IrtEru/csibv+vZOYvVREdPYYKFkSR7M8r+fw35wbscXhdIYqwfz/ttZ34tFXT2NhzSpHJQKNT0Jk4GQoKUDx8PxkzNNj0gwi1DOEP48R/b+Dcvw93e0yjgWnTpH9HRgmSeM0YqnAbLsaNkXEGRhRpOVdNaGYMggDZ2eB7ch/WhrauY66y9DUaKeavaqyis9lCQ8gkJqZ5ZwJwigKaaRNBJqN49ddwyiVXxJEjEHFmKwqrsburV6lk6hwtlpBotkc/gV9zGaKhk9zJD6CMjeh2brMZjh0V8d21waVKHYfJisEnnIVfnTpyC19UFFHfeZjIr95JxIJ++g3JZGR+dT5Lf3/L4CTJB3A3qHyVLPzJMh7+gpxQD9OBPEEm61pjWkr1dLQNrZtBFCE/x8qJo45Be2AcObkoXn8F2fGjvPiiVIl2Q6BUwgMPEBKrJT3JikqwUVTU3WlQUyN5R4p9ptJx9DwcP47m4btROYa/IsYVAtMj0Z8t7/H4rFlSzpNGgxR7crU1+Q3EuDEyzsC0t6OvNhA7JxpRhLwt5QS2ldFR0So939jYXaAKaTfs01hBUzOEzk5yK1+yv8ldJgP/5lIsEfE88W1/1AEaRBHC2i4Q1nqBQB9rj86oDQcvUK6eyJqMSjKd2ThsItPvn0DY1O69RI4eheCSk8gqylzy8ct91Cz80z0Eho2shn1AnD9pD2QN2BlNq8UlTYdrEUUw1rXDrl0ufS5hYSPrlahbf5TK37+LsXLopFIF0Yli/YdkGI4N+r2KySmk35bK4uRqVs9qobr6Biq2CAyEe+8lIlLg8Xs7kcu7i9JlZ0NLvY2q9w6isBrh2DGp2Zy7ymPDRPT8BJzllXR2dA/DREbCXA+1Jm8Uxo2RcQZEn1dNoxBOcrqKixchIGc/AG1lbdIBBw9CS/dGVkolaOtL0Tv9SFnpekzA6YTz5y/90YfPuvlECf6ZSWg0ktEjOOzEl+xDFGFOlqV7exaHg8YjRUy5JZ6Miq2Ey5qwh0czb4GMSVepp5vNUHSyjZSSHT2S6MYMQ2EBiCJlHxyn83f/kIQ5xkBNbMZ/rSbjN4/iExcydBex2ZhwUwK+eSdpvNg2qN+Mwt+HgK89QtDdy5ks5DF79uClTKxWxk7STEoKrFhBTJCRp5/unoo2YwY45UrqMlag8b20o7FaR6wabCB0yeH4+suoONZTlfa6UJkeQkb/zDLOiFN7shp1aiwaDQQojYRnRRMWIaO+XYu+rBXOnethjCgEB76t1WS9+V0iM1zv2lVRIcljGOs76Nx1FDo6oKGh6wCnk87zZUTMS6K09NJjgkDFtFvRBqhQrFiKUtE1CXfkltPQqmTyFBn1YjjOtnYip0f1SO9QqeDW9CJkvlomTpIhOsfIRD7UCAImXRiKyFDIyhrp0bjGcLhl1GpYtAjb418i7ydv8+FLbYOrThIEWLoUpkwZ+Nh+MBjg2Hc+4Oj/7oKLFwd1rmHlUu12QED3jyAyUnKC+KdHI6y8SXpwKMrAvIVMhu+keBpO9AzVjAE7fkQZ/3jGGZCWc1WEZUpu0YgkH1p8YvGND6Fk7kPUfXxIcmdcY4wEB4nEfetOhLBQt9aGggJJCqPq3QPU5zVLXperOpO15tViMgtEzYhi69ZLm7+zZ2nLKUeVGifVeV51wbLtF1BOnoh2UiIdtR00q6OI+VrP+luZDKrCZ+CvtRL81QcQwoYx4WGUk3FLEkHPPjEyCbrepq0N0eZup8e+0VcbcCjUKA/t5d13vdAgMTBwUC9XXjiPs7Ia+eEDiA2NgxzMMCIIV5I6r50vZs68lGIxf74UohnNxggQOiOB9tyKMeOYGi2MGyPjDEj6d28j9db0K3/baxsRIsOpKjLTeq5KevAaYQeNTkHSbVPc2qWKopRNL+9sp2nbKVoL6uDUqW5+25qDJSgnJFJVI6O+HlrO18LRoxjzy9FNSexxTv+sZFIfmEldpY0QZyMRP/4iARMjehwH0J5XhU4nSBNeRO/HjAk6O73fNngo6oCHmeJi2Pir09T9+zMuJxbZrU4MFS0DvLJvQjPCWfH2F7nte+nMzbK41YRvKFBPS2PmqmDUaoY0Z2Y4mTIFkpOR5pI77+zVKC7dUUThO6eGfWwAdSer2P/Ua1f+Dp8Vj665nLracWvEHcaNkXEGJHhiKL5hUh2sKIJY30C7Kgyz3Jfjgaux6YKkSWKQNDRAayvElh6gvsaBIjcHp9UOev2VYyx6MyFzU6+UADZ/uBtHaztiaRmhMxN7nDNh1URi58bQfKYC30h/Eu+Z1ef1becvoJyUOrb9qRYLfPjh9eHF8DLh4XAmaAWy++7hcl13e24F1X94B0vVILwIgoDvzHTSM9XSojmSKBSovvAA01ZHIja6L5s+GlGpIDHx0h++vr02FTI2m2jZ0Y+u/BASmBCAs7ScjiYp61geF01IgJ3yk43dNHbG6Z8xPOuOMxKYzaDSN9IkC0PnJxAhb6LeEeqVUjWlEtatsoOvL/4qM5r2BtrbnN2MkRk/WEXGY7O4cAEC9BUYcy7SWdaIWrASMKnvMXSeK0GVntynp0YUQSi6gO90NxvLjKbZxm6H994Dq5XWNoGOjpEeUD9423PjAn5+UtpL8FUpTMEzEkn72zdQB7svglNdah2drniNBtVTj6LzuXGEtYKyEnBU1SGahj/7XBPmhzpER/VJKWm1vVOOIjGWigPl7PywddjHM1YZN0bGcQt9qxN/SyOL7w4nNhYyY5qImjrI/IqKCkBaJNS+ClpCJxIc70v5wz/CGBwrbYuuEh/o7ISlS0Ria44TGafAWKtHHRuGoOg7w95WWIIus28dDtEpEnvnbIJmu6HO2N4OOTmU98xVG36cTtpe+ZiiHaVsOh7Gli0j1CNnAMSWVkp++h9slUPXTbi/lILly+mpkisI9KqA1w+dBZXkfuMFdmy0eM8gEUXvVcDodHDXXTeMrGtYij8GZRAd5ytG5Po+qdE0n5MEYpRlFykvthN0ZjeqvOwRGc9YZNwYGcctOirb0GqcKMKDEQSQtzUhj/DcGHE6RMTNW654GEQRUnT1EBtHhEZP9Nw4mD2bq1t76nRSDLkw4y4iw0VMN91K0KLJ/V4n/Tu3ELWkb+VPmVwg4/HZqPw1rg9++3YunDZ4pfnvoLHbUWemU9QchD0wlHvvHZ3RpiZbAOs7V/Hqzri+ugkMClOLiV2/PUHxhd4XYZ3OO9dxhkeSfMdU1PnZnDs3uHO1tcGp7c3UvrAeW3XDgMe7TEjIqC2B9TYKBTjjEqg7Vk5tz6raIScwI5r2AskY0abGkBXbhNJuQlQNskb7BmIUTlfjjGaM5Y0IlyY5QQBFW5M06XlI5YYzWMpqoUmKb4siaNvrMflHoG6rlxJJ29pgz55uu0YRAV9TE8jlJD1zOxOeWtzvdaJmx6IOcMPQGIiKCloP5HL8oLW3EPbwo1KhnZdJ0p+/zYrnslApR2P8AMIiZHzr93Hcd9/QRLhy8+UUNoey/j3z1UVYXTgcOGyDD1/4BSuZ8JUVLP3WtCtS356ilDsp/vcOqjfnoGh0YSUdlbGhnjgdwzfO3buhTpNIwdayIQlPnnvhIA3n+84rCp8eAzU1UtdwHx8iH1oudZkerGDMDcS4MTKOW1iqGpFFhQMgc1iRG9oZjO635cXXaG2yY6uRbvTLxog5IBxVWwMG3wjYsQOqq7lWWlXXUSsZKyMg99m5fgfnz4PMZhk5Y6SXWTctXcBPYYKqqhEYUE/q6sDZ0dmt2kqplKSxgweQn7Hbu0uD1xcbaGrobkg4nXD4MGzcKOXtolKx7MkkYtN8+fjjnl1gcz8rJu//NnuvUdkge4zYO0zk/HYLlgY94YsmItT3Hb6qKWin+KXd3byEo5Xy3cUcfOLlYbve7NnQrEvAz1CLn8ri9UZ0nedKqD3adzxWmxJNqKyFikITBgMIs2eRuigChe+4MeIq48bIKMXppEe57GjAXtOAKlqSHdcYmnGqNG7H2y/TebYYVcE5qgo7MZZfMkacItr2emwqHXKriaO5OmyfbpTUnJq6VwfoDHUMrtFK74jipf+pru7zmFq9D3aZCrljhDwjRiPs2NFzzjWZ4L33aDUoqRu6tAyX6Gi2kv/f73D+a39nw5t69u/vs9FzN0QR6gvbOPWH3chsliuPHfn3WT55qbu7QyYD8+7DlOyvYsIEaVHKyoIHHoCnnurpfcm4cyKqu27BbhvaXfu5T4s4/sKp/r8DUUThq5aEBO21kv5NH4k+1eV26v+9npb1+8nf3d174jBZKdxbi1hc0utrR4KQSeE4q2owNg9PDxl/f5g91YxV6UvQvvWDMsbP/fsw9dndP2O/1AjaCuv7fM3Fah8c/oEc+biGnBwk8bN71jF93rgx4irjxsgo5fRpYPv2UZeANu17a0h5cDYA6o4mbAGhktKjw+F2gUTVpmxafWMpbvDDpJQ03IVOA3KrCafDgSMgmPb9Z+gsrcdhMHYzRkTxkmdkCIyRgkPNiEXFkJfX5zGhqYHURs8k5fFF3eXnhwNRhA0bKM0zUX/1/Oh0Ynz7EwqPtPDOBp3L0TNvef2vNTR0wSomf2EG1aueRJaUwMSJ9PisrrW3TcU1HH3+FMGJ/kz/6twrbm6zGdTLF+CTIBnCV681056eywPfie0hEKtQ9MwRkckk75FC3ZVL4fVu7p2daN99Bcdf/s6J7VI1RVuVgZqtZzEaobTIwal/n6Rx4zGQyZj0k7uJXDIRub5FUiLthYAQBdu1d9Bq9UVsv8oj1tZG/d/ep+YXL9J2MNfLb8Q9LI3t7P/au5iMIrooP2RhIdQcGb7s7nlBhfg6O1CX5PeSpew6HbnlNBwv6/ZYSEYExtL6Pu+V0FCodkYj1Nag5lJjocRE/KclejyOG41xY2SEEMUeUYcrmM1wYIsBR14BI5KN1Q+6CF98wqTd2xVj5MQJWvPrunrKuIBos6M/VYyxw4HRpqQlWdL/kDfVY/ULRtXRSodPBK0dClqtOqqF2O7lw6IoeUYiI/u4QneMehctJVGk+qVN6D/b262k+Fqqj1YSMTeRWTeH4+fn2qm9hfP4SYo2FnCuUNX19q1W7OfyyNtZS02twMJVPi7NxzYbFBUxaIvEZpPi9leXsggChC9JZ81jEdx6a8+vqqFB6nt2NTklfuyqzeC9D2QIui4vgVYL69bBo49Kf19taIVGyD3WqDM2m9j2TrMU6/cWvr7E/OX7+M9Mpf5YGXW1Irt/dZDC363HYbZRkmemfv0R6ndLN4xMKWfqr+6TBDX6CDnqdBA3JYDzk+8n1OeqiSMwkOjJQUycINJQNbLd9dRBPujqi8nZJW0afDISaTlVSlffhqFFs2IBCZmB0kc4iFwNTXw4pvLuicShkyNQ6xtobur9PgnqqCB9goOo2tMEn93b9cQgjKIbjXFjZISoquKKcNe1lJWBX9k52pqdV8peRyPJaycSvngiFBeTvbGKVjdK6sXmFuLXZmA0CwTF+V1Jf4iZFkL4w6vw9xNpVMcS1lRAe70JQ5ujmyqqSrSgTYuTlKwGwunk9N8PubTeWrLzsR4+SUt2Rb/GiL66k8nr4gc+obfp7KTs83NUVUFknLJr7dq+HUV0BPE/fQzZQw8Ql3Dp1h7AXVVZCWdP2aT2qJcxm3E63XPKZZ9ywIbPenWPXxnjVWMRRdi6Faytnd0ModTpftzxoJboaMlQ6ctrMchUjStjOLLDQMOOHLZu9q57RBsdxORXv8fSxxJoahbwu2slLUEpaPT1xKX7kpP5GHHhlivvXaZWDmhYZ2ZCe1ACgbddk6y9Zg0xMyKIjxhhmXSFgujZMVzcVYG9uJxYqhCPHYezZ4fn+kolsV9aK/17EIrBuuRwLJXdjRFFZCiBWgvFZ9p7n5JDQ0nXlBEoto7niXjIuDEyQmSfEfuUji4uhsj6HBobGdXGSOzcGELFJjoNIo2nK90q1ZRFhqPXRCBTKdAvvPnKehQ2MYj41enMfnYRwry5lMy+H5nVzMEJT3ZbzAIiNMz7+6MulS62HSuk9diFgbPsRZHSN/YT0FJGc7W5X2NkzjvPEJHohRXRXXx9ifvuAwR9/SEilqRJj128KCU1yuWETwlnyZfT2bkTjJ0ifP55v6crKRYRNnyGvU1yDYhNzZS9c5j1610vDXYazdhffZP04EbssYm9HiMeOdot7GU2Q5y9lLjWs928AaGhMDW5k5tmt7No0dCWJwsCzFwbRviDK7hQJPN+Xzm1mglzg5k8GRYvV1Ax/wEUvmri4iAgPgD/L92P02yls81G66kSLE39/0DT0iTJHdW09O5PKJVw771o1SMsciaKRMyOJ9xQQuGJdoIjVZiMIiUHqzn+k8+GZQhCeprUBXgQnpHAieE46hu7Ncs8fkZJqyyE45/Xd+vbeQUfH+RLFpKaCjJ/L9WP32CMGyMjgM0Gdbvz+jRGqvPb6fCLpqlNgUOpHr2lfKII2dmUl4N/e1V/a7ekVHYN4Ro9MtHBgluDe20Iu2KVHEdVHXKlDGPCJI8nmLL3juLT2UhLU/+TtXixiLKD1dRrEjC3mTDEZ/TpHlCoRu7WUQb6knl/GvFrJkmxvs8uTfSXDDNBkPJYc370HuLRY/2cCTrOlhLeeJ6qjgAM9Z0c+9Zb7DqkYcaMgYuULv8s7XI1CTdPJv0PX+z1cxFF+OhMCo5JXe1YtVpY/mQiWV+dd+WxsjJY/4mTN39dxoefqaiqkvJQevOONDRIx+fnd/VRdDrh3Fs5nD3S87fWF4GBUvjn2WclA2kobjVBAI0G1t2mQAgPQ6uFVauQmkhq1Oz52R7OfvcNHE2t/V5foYA1a/p4MiwMVqzw/uDdoaoKISebTMV5ynYWYVt1Mz6+Aq12P4znhydUgyBIX+gg2iEETwhBtNppr+ya0DIzoVMXga+hvm+v3Lx5hCbqCE/yjtqg6BQxNvURy78OGTdGRoCC8w7i87fRXGfDdE2yucMBdz/hT13UdKbN1WK/5c4RGaNL2GwYVt2FwwHFE9dh6ewnJLBrV4+HTGUN2EQF0ZMC0PQiAWK3g5++gk5lIA6Z0qNEQ8OFGvRny5E7bejL2/o9tqJSoDUoCb1fLOGJvthuWjt6RKN6STISBKCjgxZdPAW1AdjFrrEGNhcTuvFVcvJV/X5ut3wziemvfpuEJQnoAuSo5mQRPi2yqxdIPxw+LP1eVWqB6Dtm92m9FBWB2S8Mm/Oaz1IQur0m7597qXh5G0er48j/tICXXxJ5+WXJ6XPtIv32P/W8/rpklFwuEd65Q+Tt3EwKKt1fDCpO1DMlvAFBoNuO2JukX+XQmHBJf08QIOi2RQhBgWht7Xz+ahPF+X2HW/qN5MTEeGegnhIXB3FxBASA0anhd69HUhs7mwvtkbSVtWFvH6aFNTR0UOX+Co0CWWgwrYVdLhC1GtKXRqDrrEcj72OeU6kQli9DFewdz4i5zczxe3+PWT+yuUDDxbgxMgJ0nC3FT2wnSVnVI8Qul0v3klo0I/PRoNYII6Kj4RIqFbpgFRFxKuQZadz3UB/JWs3NiKdO91hM9RfqsPoGoQvq/XVKJUzQVGHyCeGrX/Ws6qHlSCHacD+UfhrM5X2X5gHYElKJCzVjDo1FnzxdEi0aLZw9C7W1PXfOEREEfvl+kv/8LRR+l7ZsDgcxuVupFyJRpCb2G+pQqQV8Y4MQAgNAo2HGs0tZ+WXXur21tsKGDSCaLb26FEQRDh8S2fjPCiZPpleD8zINDTDrO0t56LW1fPPH/tjSprDuZoFvfUtyql17C8TFOPnCF2Dp0q7n7OcLaKq2sHu31C/QVfR6MDnV0NCAoc3Oke99PKzeyClzfDDech/WDVsI//B5Nn3QyZ49o66QzjVWr6alXUGnQ4PVCnuF5bSoorBoA2krqOtfq38UoYwJp73oqnhMYyOpYXriHGUE7t/Q9wunTx+U7tLVaIM0CGol+sohkCoehYwbIyPAAv9clEpYllBKUlLvx6gx41B6UTF0qDCZ0Nt8iIiQXN69cu6cVIJ6Tf6LuaIBMbT/BFRZQx3WoAh8fT3zvMY/tgx5kD/qu29h+q397xxTk50Irc3ERtgImexalY7L9BKmchmbDXbtoqLQJOURXYNMBiofRZcXRyZj6m8exvqlbzDh2VvdvpyryaGhoXD+lJmc/7e5V4NZFMGnsYwwWw0T++g/aLHApk1w5gyERwiEhQukpMDXvqVg7lwoKaFXuf07ngjq0SF3/pOT+PuLau66S/q4XVn3rFap3DhrWSDC1CnoAhU4lqxA7DRi6RyeJogBATDrjhjUD9zFvHnw7a/bWb589Djl3CIwkJh75zN5lgaNBhInaUEQUAVosG7Y2m+5vLewdAze4LlcUdNSeOmGCw5GVlbCpDgDKnU/m0O53DvZ1QCCgDzQH0PNuDEyzlBgt0NBAXY7+NSX9rnAqp1m7GPEGGmzaPsurRRFnNlnKSkB28Wybo87rE40y+f18UIJdUQgqoWzPR+fIGBrbMMvPghVaP+CIB2VbVgtkPb0EkKXZHh+zd7Yvr13eXJXOHKE2sJ29m4xurbpEgQ0UUEs/+Fc1PEe1rz2gSh2eahCQ2FadBNx00N7dSTIZJB1ZxJ3/XZurz1hCgvh+X+InDwhMncunNnZzPO/auazz7qKpA4ehJaWS9fNOcext6Qs094qJoOCwNpuZr5hBx0vv8+f/8/Btm30WuUlinDggGTsXGtHLbo9GKNVwb6vvz9s3onQUCA1VdIZGYGOxl5l8WJmrQ0jM1OSAfKN0BEp1mGpbED0HdrkzqZztRy678+DcmxVHSyj81QBplN5XHjlgPSgXA5LlhAYCLqY4VM5VASPGyPjDBUWC9x9N2Y0iMuW9+kOVjnNOBRjwBgxGmkx+/RtjDQ2UmcKwOhQ01rRVS0gGk2YZT5kfHFBv6d32kXC5rvRSfcaRKsNW1snQUmBAx5rMzvwWTSDiWuTCUgN8/iaPaiuxngkh/073d+xiR0GSt44SGEhxIWY3KouGSi619LS//O9rYktLdICDlKzwtu/HkvInYv7vZavrvcngwMchBUeJGOyQGAgxCfJSZkVxL33Sl6w1lbwbSon2NGIXg9CSjKpy+P6HfOJHBXvn5+CfdU6Zs2VEx3ddw+c0JLjpKb0vP9MbRbyzzuZ8dOb0TdfauDoFCnbWURF0cDfYXGexfP+KMuW9VSGG2uoVAipKdx+u6QHk74mgY6IVJqb4WDO0IryBCYEIDObaG/0PM8iZkECDocoNZ+MCOx6IjMTgoOlkOYwoQr1x9wwboy4hCiKiKO12mM04uuLQ6XFKipRT0ruc8VQiZYxEaax6k3orf14RsLDOa2ej0UTQOHku688bGyzYo9LJDKh/wqZ6C/cRMzcWI/H11mjxyYqCIodOKkxOC2Mub+6xeNr9YXzwCHy80HRPsDq3xsOB4FfuA1LxnSiEvv4rDy4/yxmkV0f9O2qEUWpJdDlfxtOXwCkSFtOjvTgYMtuwyLl3POnhVdER4OTA1mzTnbllggKkmTdv/o1AT8/EHS+hMT0f0/IlTJm3x5FynR/broJpk6VCk2ufXNbXq2jNmxaj1iO0wl73qrm5FsFGNVBBIdLrsvCQjj4ZikXDvbfVddaWU/dd37PB+86+m0E2GflmVzuvdbCI4kgIJdLtlVGBmSH3ITBAHbN0L43hZ8WlU5Fa2mbx+cQZALRDy4FQBN5leEhk0lJSsNoLGrC/bE09Fem2B2b0UZriRuCT6MIj6eTV155hSlTpqDRaNBoNEyZMoWXXx6+xkhjGXOHDadc2W9Cn8ppxi4f/eI5bbVGZDqfPudPgwGqS6045Coqa7qC4L4xgSx79YkB4+KJqyfiH+35BNZapkcIDECpGqEk4JYWKrbl09EB2s6mgY+/BiEwgOClU1n9/B0kPjC35wEWC7bT59zOCzz64lmpNrYPTu/RU3taUv+tOddM47s7AckYadx7Hkt7/ztP0dDp0ph8dLIriv6CIBk+589DzUeHpccSE5CFh7qcP5GcLG1g+0UQWD7PxIq1qh4CVTIZLHg0Gd85kzl+vOvxtHQB2eqVOPz7z2pWxUUw+6lpzMm0XPEgdaO9nRN/3M9n/6wemwmqbiKXS2v35JVR1EdMwz/Ssz5WLiMIKMMDaSt3fQHvjdTbJkF4OL7Rgd2fmDoVW2AYjbn9J8N7C98of6xNrntGao6Uk/P9t4dwREOHR8bIz372M5555hluu+02PvzwQz788ENuu+02nn32WX72s595e4zXHdZOG6JS1a9SsMppxj4GwjTtdSb8I/pO2BIEWLXEgjZQzYL+IzJDQlB6BCnPuJ/E6S0aztZxrjUWozYEjbnN4/MIAmi0vSSJHj/B8fU1A5+gpYXy85KwWXGeBcvGHcjtvRsUNdUiFf/ciK9cankrF5zIs6YC0FxuIK1oExfK+la4rN9fyJY/Fww8pl6QySAhAbThfh55fBISBg5PORygzUjqU1EtKAgefUpFUlJXVY4gwC23CigDB/awqe68malZ8l6TdltawLrnEG01Rs6cGfBU1w2LFkHpxDUEBA79pkATHkBHZdugziGTC0Q9uBS/uMBrnpDRXGkk9wdvDur8ruIb5Y+9pd3lW8E3VIvDYBq10lT94ZEyzAsvvMBLL73EQw89dOWx22+/nWnTpvGtb32LX/3qV14b4PWIxWBDrum/Z4FKKeLUDPEuwgt01BsJiOk7SdLXF0SLFYWPyiXtCm+ji9ShixxGt7fDIXX7jZek4gMXZBC39Sw1ygzsM2d591pWKxXvH6axKb5P9WtRlBbShg/3cso6l4TJOoI1RpoWTMYnsnd3s8LSSWikAnO45I6InBoGU8MQRXjwSzrstzyJX3Lf+xj/qQlMjxU9VuTW6YAlUz17cX8YDJS9eYALKetYvbr/QwUBZs7s/liAv8i8eS4spv3sMoIT/Zn5vRWI5XIOHZK8ODdC+5KAAJgy17fvijsv4hsTSE1Z26DPM+GOjF71BHzDfMBoxG4TUSiH0LgSRfxiA1AY2zHV6fGJ8BtQktg3VIvMYsJqESVZiDGER8aIzWZj1qyeE+vMmTOx9xcoHQeQjBGFtv8ZaMnf7xum0QwOn8wJhCb3XwZr7bAg9xn9ISevcOECzTlVhFwyRlQqiLx7ATGBfoSkenfVadp6kvICM/7Bbb0+b2k1Un5WT1SsnIsfn8Pv1klADEHJQcz9xbo+d0/hyTrC//EAdlv3AwQBfHyAlH6Se9vb0eq0aPvQjnGF5lorPmV5aOdneXyO3jAKvmxrnUPdEZg4EZeNY4sFNr5ch7Ywm3m/WCt9Bp4girQeLeT0cSUrvhrOFIfUtbhHTst1yuLFdPvsqnYVQlAQsTNc6C/lBn5xgZiPVksyxIMos5XJhV7rq33DfBBEJ4YmM4FRQ9cSQjSZsX3yORrM1P/hDfx/8q0BO3FrgrTIBScdzVbUMWNrzvUoTPOFL3yBF154ocfjL774Io888sigB3W9YzVYB/SMjDr6KA9Ie2QWcfP7TzC1dUqekRuBjoM5lO3vrqcSOSeesIlBXu+zErpuNrH/dS8Rj6zs9fnCN4/Tml+HsVaPIyoWf5/uG4WBwhlu7/pEEXHjpkGJ9On1sGevQFNr1yJQ/ZvXObDbNugcCx9fgceeDWH1anjvdQsd1a7F4tVqMAdGUqFNG5wQniBQu/8ibUfyaTDqCAy8cQwRkLwjV3uB9HvPULilt8SaQVBeTmDDBXzqS9G/t6XPzuiDQaZRodAq6GwYhHaQCwg+WnLqI7Hb4UxZUL85hldeo9WgVAl0No49GXmPBfxfeeUVtm/fzrx5kk7EsWPHqKio4LHHHuO55567ctyf/vSnwY/yOsPaObBnZNSxdy/iqtW0GtVX5LddxdZpReE7Ak3lhpvOTur2X8DeKkj1pIPoj+ESSiXJt/auh2Ix2Gjeehzl7OlEfHU6EYsmYLMObSBZROBT4W7uHoRaV0AA3PuQEugK00R/7xFilNJn6YkK79VotTB5MmzbrKA4t42sGNcqI7KyIJukQYkhn9hQiz8OJs3yoayMvivQbhAiU3zJOdCJw+E9gTcxNo78I22oHCY2HAjinge8c95uCAIync+wLPhJD8zhwtFT2EMj8XWly4EgINdpMTabgNEkIT0wHs2Wubm5zJgxA4Di4mIAQkNDCQ0NJTc398pxwmiVMR9hREGGKsg7zZSGBVGECxeo1yRSqJrK0qXuvdzeaUEdPHy1+SOF7Uwu9bVO7HawldegTIkfmYGIIo2bTyBTKbvpog91RZEgwILlavDyZQSlF426oiJqHaksXSEna7nr1kBaWo9uBj2wGGxUV4lExKl6XThKixxE7jzH3Le+hf06qN4dLMFxvviIBsrL6aGm6ymCXIZywWz81/8Mc+rNXhNDvRpRBIWfD6amTvR6yYAeKqKnR1CUnIgqzvXfqsLvsjEytvDoLt+zZ4+3x3FDMeXLI1BWMhiamqCjg6pt56ma7n5iYeTqaahDrv/Zt6AlnEZdEkafUJobHESmjNBASkuJ9W8n+uP/wukY3rT6fhu5jTCiCHvfrCLpsSSWLXNvK65Q9Exovfq8J96+QNtP/0CJMp2bd32nV2PEZ2IsfqYZqCMCGVvR/KFB0PkSF1xPYb6T5F4SoptzaynfX86Mr/ev0nwtqQ/O4uwP5ShD/YekrdeBA2Aw+1J3wIiYTq8dx71J9J1zsHa6Hs9T+GvpaDV1Za+PEcYVWMcZmJIS7HbozL5IbZnF7bKxhJUTiJweNTRjG0VoJiURHOQkfGYc7SF9NB0aBhwnTtN5oZqqaoELRTKKikZsKKMKQYDQe5cRFin3aI7uK+dHECAgK4nSmEXI/Xz6lP2PiIDUL9/k/oWvwV5Vx/4fbCLvN+sHltEFaG+n6PVDnP34IuWn3Ne6GRIqKqCkhDhlLZb1W7q1GbiMoG+jbluO27lCCp2GzrBEtMFDU404ZQp02H0QjJ3DYnwn35xO4swBMlcvc+QIPoIZTfbR3ps6jWLGjZFRzqhYSPR6as2BtOjiUdZXuTT/3YhMmABRN88g6+boPhvDDTlGI8a8Mo5+3sirLzs4fXrkO8uPJqZMAblox5JX7NXzpk1RMvP3D3Ig8j4OvZyP5UzPhnBZWeAXNnjtIEVIAOr8M2hLz7sUI7DuPohi/27a/vkOe7eaB319rxAVhVhWjp+znQ6nLx9+KFUWXU1QhAqF00pD/6K3PRAEMCVMIjJsaFTlgtWdhCb6orEbCLO5oPEzSGQKGakTXVyq/f3RmZuQ11aNbjdlL4w5Y+T5558nMTERjUbD3LlzOX61TGIvfPjhh6Snp6PRaJg6dSqbN28eppF6h9OnobLU3neDjeFg1SrsgWHYJ2YQMifF84ZvNwAT78skbJJ3Woh7hEaD9rmvUXPn11m4QOThh73XRPR6wG6HE4dt6It6aX88SGbMVxM0IRRri4HGvJ7n95qeiFaLYnI6EVnRLmV+yqdPw6B3YBMVVNiiRnQquYJSiZA5jYoKaPWJIS+vp8adoFYR5GulxoP13qHxJSPF8/40/VJczDTbKSa0nUBeWTY01/CQ1vA0zIKWDqcvB8+PrQTWMWWMvP/++zz33HP8/Oc/5/Tp02RmZrJmzRoa+jCdDx8+zEMPPcQXv/hFzpw5w5133smdd97ZLcl2tNPUBNmbquHChZEbhCCQNFGJAjuzZkkegHFGKTIZigBf7nzMn5VrFV4vJx4tGDullav++Y8wt16TrNfPaqtUwuLVWsJv75mHMNhF+vx5WL0avvL8NGIXJQ7uZAOQet90fCa61rNJHh/DpEUhaCfE4kDutqdhyJg5k5QUIDr6ykNO51XhGpWKQB8r1dWun/JSrj1OpYr6CkvfPYAGw6RJhITLCQsVR53b0TdAwXHTVOqVsdTWjZ18ERhjxsif/vQnnn76aZ588kkyMjL417/+hY+PD//5z396Pf6vf/0ra9eu5Xvf+x6TJk3i17/+NTNmzOAf//jHMI/cM5xOKSTcdKqcjkNnR3YwCgVWox0fnzGVEzU26Ry8foHf0DZHHXHeeamTjg7YrbkZwafL9WMyilz4yetulwA72jv58Hcl1NZ6PqYJE+CWW8A3WC3p0g8hAVlJUo2yKwgC8hmZzLk3nqQkqB+itip1B4s482o2JlcLOSIiUGRNYd29Xdm+1efbOHbrr0EUsYgq/DVWqsrsHD7gWshFEODECbCIak4ctKDzHYIEbqUSWeY0YhNk3Qyp0YBKBaGrptMeEHel59NYYYiFELyH1Wrl1KlT/OhHP7rymEwmY+XKlRw5cqTX1xw5cqSb5gnAmjVrWL9+fZ/XsVgsWK4qh2xvl4SRbDYbtt56qg8hbW2SQRJgrKDiYBlJ93RcGcuwI5djs1pRqWy9tpa/Ubj82Q/ld+DcvhP76ptdk1P3pkjDGKCzU/rcmy1qcnJsLF6jRCa76jcpQMHCx0hyuCmSplFy+xeDaLV7/vuWyxneeyMszPULZmRAayv3LrBRUjK4cfZ2DxiNUJtdTcmJZnKEybisfbliBYl+NrKypDHV1tnR+onYOjuxr1/PhTKB2LpXKfR7nNnzXLMwsxynKHG0ky6cw3lOiXPKFDffoQtMmwaVlThhmL90if7moUkrQjmRr2ZR+OiYq12dKwVRHBstdWpqaoiJieHw4cPMnz//yuPf//732bdvH8eOHevxGpVKxeuvv96th84///lPfvnLX1Lfx/bgF7/4Bb/85S97PP7OO+/g47EO9DjjjDPOOOPceBiNRh5++GH0ej3+/n2LDI4Zz8hw8aMf/aibN6W9vZ24uDhWr17d7wc5VBiK6jn6g09YvsCMc1IaO4BVq1ahHObuWsZNe9j4qY17X1zdfx7CGKttdxebzcaOHTuG7jvIy+P8bz6DpcuY/PT8Pg9rbYXAhgsIp07Cww97fxx90J5XxeGKWNauHbZLduPqz7+mRklIyKXGetfQVGEkWGhFFje6YvrXA73eA7W16I+cZ/9nbZgmz+L+7yd6dO63/tnBmqJ/EPZ/P4ALF3B89CmftK8kYOXsAZsbXsHp5MxT/yB9ggPtj/9r6Oajq+Y6Q6OZ7Cf+zIJPvoNMPfStLwaah2pqRk8E6XJ0YSDGjDESGhqKXC7v4dGor68nso8SpsjISLeOB1Cr1ajVPSWJlErlsBsAAIHJ4RSl3cli60eo162DLVtGZCx2uxINZtTqvq9rt0PnqXwC5k0axpGNDEP1HRjyKmird+J3Khfl15f0eZzFAoffrmKRogyFyQTDYCi3V7Vz4nf78fvioyiVIxsaUiqVpPbTeDAqJQC4/lV/R5Ju94DDQWj+MaYr4awhCaXSvSz3yzojDY1KArVOlAoFpKej1CiZOCWS+oZWlErXG+rFrsjA36cNj1tHu4nTYUNmc6JWq4a1DXNf89AQpyy5havz5JhJYFWpVMycOZNdu3ZdeczpdLJr165uYZurmT9/frfjAXbs2NHn8aMRQa1CF6LG1GYZUY+D2a5Aq+y/3KClzkrNq9v6byDicnbb4NCXtw26sdpI0FRpQq5VYpD79ytoFRMD5ouVnM+X4cgZnuow/yA5qqnpJHaeH5brjTOGiI8HjYaEBFBOdl9kp7kZNn1sJqlsD1YriJu3SPPdjBkEKw2IGz5363zRa6cN64pst4lS6tZ17BUeasaMMQLw3HPP8dJLL/H666+Tn5/P1772NTo7O3nyyScBeOyxx7oluD7zzDNs3bqVP/7xjxQUFPCLX/yCkydP8s1vfnOk3oJH+IdrMOstg+8SNgjMdgUaef+JSK2FDTQVtWHOLuj7oL17h14zxeGg6e1to0Mwzh1EkcTv3sv8T77PwucfQQwK7vM7l8kg7pm7ifzB48jn9KFT7m18fYnKDMdQUDk81xtn7CCXw4QJyMJDWXa3m500kUJtp/M0aNobqK8Hoa1V0uBfuhSV3IHa100nfnS0pHA3TNisohS+9tAYacqpZt+X3/buoMYYYyZMA/DAAw/Q2NjIz372M+rq6sjKymLr1q1EXGp/WVFRgeyqhIYFCxbwzjvv8NOf/pQf//jHTJgwgfXr1zNlGH+k3iAgXC05FEYwNTp0wUSUif3H3zuK6nE4oPLj40yY0Xs3WUpKJEGGzMzBDchmw15VR5tfHKHXaow1N2PJzudCRDNpaS7KKI8GBAEEAYW26zdsOXgS9eI5vR4+eXEwENxTLWoISV+XhHDz0ErdX7gAolMkJQUUyt4n95a3NhPxxO3jO9H+uHCBxn155J+1seSrGa6XAntKWhrodHiS569WSxGVlvB0EkKrusSMNBoU2LGJbi5VgjAsocvL2KyD84zILCZMNa3eHdQYY0x5RgC++c1vUl5ejsVi4dixY8ydO/fKc3v37uW1117rdvx9991HYWEhFouF3Nxcbr755mEe8eAJDFdJxohliBQFXSAgOYT4Rf13oTWVSfk5jSfLcdT0rFYydzokf+yRI4NeQE2FFZT+79v0KsDb0IBeD6Z9xzG7oH7tdHbZedYWw7A3l+uPsg+PYy4dQPwir6f0+FAxHGt/QgI0f3YQeXHfQn/tE2YO+WBG0BHpHfz98b2YjZh7HodxGOaO1FSY5Fm+mCBI2jhxK9PQaODqfgoK7NhH+b7ZbhucZ0SjdGBHMSpKcUeKMWeM3IgEh8ow2NS4tLKOII6EZIzRKShvXoXe2lOD/NCGZhw2J9TVQXn5oK5lyC7CuucQJYfreuSGGEoasFggvPoMeacH/swEAT7/XFp82k8UcuHdk6NjJXI4MFa1UPHe4f6P27+f1pLWUTHkXnE6aW1yuDzRqtWw4AeLEdLT+jwmcW7Pluqt//mUHe82eSUtqXz9GTZ+PrxGqdejl2FhaPyVOBUqmqOmDP30odFIuSMeEhICc28JlQyR4K5QjwI71n48IxfW53HkmyMb4rjiGfEQtdyOU6bo8dsVHc7Re197mXFjZAwQHAyddjUOk3Wkh9IvS7+SjjoyiABFJ8GJkou0uRnJ+AA6Sxsoag6S3tBgpC4BY34ZtHcQcvAzSkq6P6dvsqGLD8aalIasZeAupYIAjY2weTPY6pppeX0j1rP95L0ME2JzC8YOJ837z+NsvUrX2m7vMpZEEWdTMyf/emjURixsuYXs+vpHNFwcCm3uLgIfu51VD4UOuhePKEK7RU1+geBRXxRP2f96KYd/vBFrUYV3TiiXU2qMpDVuKu98pBo9MvB9cNNNoPMT6FY3Xl6OolOP0y4iVlb1+jpjkxG5zHXD0VDbwd7b/yRtjLyAw3HJMyIXEPHsJpSLdgSVoofBeOSpl7jw2djqvusp48bIGMDfH+xKDYbmYQzTeBBGEQTQhAdgbuiqK9+8GZwbN4PDQWvoBHbJVtFuVcMgK5psJZXY7ZBwYQf5x7rXscc8uZqIWXHYA0LIutW1/h3BwXDyJFw82oxf7QXKX9g0rLkYvWEsb8TiG4QlIIzG01cljba0IGbnSP/u6KC6zI5wPhfB0DEyAx0AxcRkAu9ZibOlzWvnrDtVI8l+XoWg6H9ratGbMW3c1e8xIP2Opz6Qwbe/7RVlfpeprnRiPXySomyD184pj4+hNGgmbW0uNfgdkOKPsyn4eGiqqSIuO7uu8oo4DUZUZ08S3pCLvaah1wo5U6sZlb/r3ZCtehNOoxm50jvLX+HpTvK3VWAywZE3izzzqtrtKNXyHp4RFVasDE958kgzboyMAWQyUPur6WgcRmOkogIM7k+K2gh/rI1dO+DqCgfVRyshJweroMakDqTwaNug1/mONgc2nwDq1AloOhq63/+CgCw4EFl7m8vnC7mU51qT24Kj04Tt0An0p73bZt5d1JNTWfLu11ny1leIuOmqpGuDgZZP9tLeYgdBIPS5x4j48RdHbXtes6jGNz6EoCz3Sy3t9u42x+XJetfHrdja3YvH1LWquSBLd/l4rXb4mkLa7VBnDiRhdjgZ93hPpyfhzulok6Ou5GQMFmNuCa3lQ+vhuhpHXCLncgVEQcZrR9N79f6Z28yoA103RmztJq/eK/FpWoKPb8ViFkmq3I9H3SntduTqnp4RpdOChZ66V9cj48bIGCH16RUETB6kmqQ7FkBDg5Ro6ia+Uf7YmtuvXE7Qt1FWKmLZdRCl3IkYEEiw1kRH0+AMq7h//BB1ahydcenc9OXUHve/IiQAWYfrk2ZwMMREOVH6qghQmlDq1Bg37RnUGAeLwkeFQqtEprjmzXV00Fyip27TKfDzQzs5makrwqRSyFGIVis5wnpTSh0IhQIOv1dBx/4zOJ2wYYP0+OT7J2Pzd69SKiJSIPPm0anI2tQEc1YFkPTkMq8m5gqRESxdJuDn59ka2Y2SEhSdehwaD75ID1H6ayE6mtagZHzDfHp9D9Z2M1p3jJEOs5Tf4iV0/jIcSanI5RC2qO88p36x21Foe+aMKEUrFnHcMzLOKCJhWRJ+sYP0s7pRdWGubZXaX7qZDegXG4C9tQNEEasVtKYWHA4oO93C/ZPPk5ShBZUKf3Fwu6vQlACIisRXX9NrYqQy1D1jJC0NHn8cCuY8hjIhGqMujKi754N19OXpOPUdNDZC54HTo3J8nmI2g+liz7yAFQ+G45eZjNkMd9whPZaVhdslpK6sP+3tUHm6Eau5p6u9vqiDs6+fprrK++G7oCBYskLhcTVKf2RkdCtO8ZxTp9DUlxOWvWNQp3HYRZoKmlzeHIXNTaYhbDLJyd0fv6zaatGb0Qa5blzYDd41RgB8syYQGgqKKa573q7GZnag1CgwGqUGqQCIIkrRilUY94yMc72xZ480216mro7KPvSrys+00NlqhV4aEPZHQKwfDqsDa2snFgukxFtpCp9EyIwENBEBJKcI1JkDr7rjPEeREIPOUNfreqwMC0Rp1OOwuzbhabWg0shYuEJNceRCDCYFFqVu2OSk+6SX+LMjIZmUXz5GzI8fHxLp6WFPlTGbaWuDz9c7qN/VU01W5qOBgAB8fLy+hvSgrQ32/DmbbZ+Ze3wORceaOXbQzoWL/XsuTuzuoKXCvRCnWn3JITIEWciCICWHDppLSR3mUNfysPqi/Fw7F555HtHumkRy9NIJdMSkk9SLvM3H/6zHbjBTWK7B2OzaxsneYULw8W5IM3xBKiGTwrvive6Ql8fFvdW0VXZw7v08Ki7nL1utyOVSmPNGYNwYuVFwOLDWt8ChQ9LfNhts2cLmTWKvSWH2xlapSuX0abf0TXwClDg1Pugr9Oh0cPN3MmhNmonMaECWGE9KCtSbAzDXtQ36LamS49CZGrFaeq6ePtGBpP3vYwi4t7LOmQONzhCcMjkNBc2DHuNAGAxSNn6vpc5Op5QBfE3ujjIhmsgFyYQn+nQtXna710q/Kyv7VaL3OvqCWtprO7nvQTmJX+3egc/phI664csitVigJm05C1f59LALkudHUB0zh5SUvl9fWgo575yn4rfvdFtsCw630FoycqJW3kiRqBcisduhOWnWoM5TdLKNoHg/BKVrYUVFcjxZ87WEX9OaRhAg+OIxglpL0B3Zjo+p9/vVbrajL2+78rej04yg9a5VmzhJS8gDKz17sUZDoqUQXUMJNrvQVR1tsUjGiHM8TDPOdYS9pZ2yYiecOiUtbno9lgvlmPLLKOilirU6eTE1Bn+qZ9/p1m5NEEAe5E9HdTsyGQgygdD0UDoqWsFux98fVOGB1Be2Dfo9aScloLF1YGvruVjJVXJiFiT0zLcYAB8fSFqbhjM6jpbC/suCe/UglJW5dT2nE95/Hxw7dvfwFok2OzVv7pIMkoGw2+n4eLtb1+4Vq5WaQ6WcH872M0lJdDh9ezxsNMKmTVDx783DJvhnscCtdyquLui4QmSSlshIqS9Qb1itUFgIa2+ykfmTW69U99hskP3Pw+T+5F1M+rEbVmtVRVDUEsyxxuSBD+4DhwOqctuISAt063VLlvQ+DWkmxCGITmLS/Pr8YhrO1ZP99RcByDttpvKCCYNTy8kT3nMBqtUgn+RhLCw+Hh9/BboQFbaE1CtVTxVFVgwWJU0tMncd1GOScWPkBsFc20pNzaVSxaNHoa2Njg5ILNvLqZM9b8rakCkYfUI5sa0FUemeZZ7+gzuInNtVORE9KYDWdrnU9x4ISQmkqahtMG8HAP8JkdhlKmzN3s3un/mFDKb8z4Mk3je73+Py99T1FKrKzaXuwEWXr+XvD/X1cHK/EfvGrd2eExx2Ks62Uf/qJmnL3R+CQPPmo9Qe6N6Q5+IZNyuilEqEz9ZTfGL4XCMBAVJOQ3a2ZCvn5UmGiI8P3HYbTP75fdJsPwxERYHQ1Ijo7HlPCALcfDN9ilupVJJERuwdMxFiuvq3V1SASrCR/I21aAPG7i43KdOfyqQ+rAIXKS4S8bO3EpQc5Nbr+vr6/afEo1ZD2KqsPsfVXqlHERoIQFTZEZznziMrukhQ2Rm3xjBkKBSQkEDw3InEJCqlt2Gz4aeyUN2ooqZa7PX3eL0xbozcIJgcKkqSV5LbGA6LFoFeT0cHBOrLaTld1sMtL5OBNSCMGHVTtzQTV4jIisIntCu7MD5BoM4WgrO+EYCpj89gyg9vHexbwjdCR8Df/4eoaa63FneVkAnBBCT13/DLumMfJ3dc43q3WGh6cwvV5a7LacbGQmuDjXMfFmDNvQAdHZLLxOFAKXPQcLKChn+8P6BEp72hhabfvozYYbjiSWh4cxslBa7vxu0OAQIDiTaXXCvjMaQolZCSAufOihz+x2nkzqHXxa784AitDd2vc/GCSN7zeyi/0LsnxiWB0Wsya5ubYel3ZxOzqGcGZkdRPQ7r2GgvrdYIaOZmEhXl2etFEeo+PkSG8iKC3TZoFWaAsLRgIlN1yLKm9XlMZ40eVZjkbgicEouvaEBnbSF+lYeVL0NBcjIxq69K0m1rI2j3xwTpbEwq+JTEpFGqaOhFxo2RMUxJyVXFFPr+vQOGwFiagydgKG2itEbaZoipE3CmZ5A5T9sjCfT++8E/OZQgR9OgxZIiIsDoG0brRSnsoQvTog7yoJvWNQgygbT7M1H6eD+J0xUcHUYaXt/SfdG2WrHUtlD89lGXzxMXB3KHlZYWqH5jl6RYe+iQVO4nFzE5NdQWdeJs6CdsJAhYw+Ow1bdQmd1EwyufQ3k5gqGDk7/YiLXFINWPDoBCAXOff4zVP541oDNC7DAM2LzR6ZT6IroSZfHzg8ceF7jpu9NR64b4O3U40AcnoQvquo7VCnln7Uz9xT0kpnsvp2DWLAjJ7Jn0eWC3jYvf+Rclf/x0xAX2XCUtXSA11f3XiSLs3AklVSriZNWS+8u3Z2jOXcLCBaIeWNKvopupTo8mQnpeiIslIAC0mRNQBg7++q5gabfQlN/Y/0FpaagnpzJ9+qW/Q0PBYiEqxIotJLJLEO46ZtwYGcPo9bD1smd/8+Z+JzSjETQxIfhpbJjq22HGDJLvmEqwsgMxIpLIyO7Hq9UQkBKKsWKAm8gFZDLwSwqlaYAcjLGGzWjDv+4Cp94pvPKY02zFYADbvsMY61xzKcXFQeCq2Tg0vnwq3M3JbAXO3XuhuRmf//4Ogf/5I9PW/xpZdGTfJ1EqSf7BfbTrorHv3Ef+J/l0/O0/tNWZURblc2ZjNfV/ede1JFe5HJqaOH7AgrHV0ufvqqZRScGP3+imuHstMpn08j/+n8jGz0Xqe/ZP7HF8UnLXLnDIKpflcibfFNmtGOn0YTNxp9aTkOTdabEvfY+S9WdpqzNzQjEfQ+fY2PlOmOCZEJzdLtnXbcowKirAkTKRnu223UcuB82i/hNqLQ16fKIuGStaLb5J4USuyRr0tV2l7lg553/+Qf8HhYaCUtkVAhQESEggLFzAZ86UUdvqwZuMGyNjGJVKKnbJPX0pc+7aJi1XkZwMd96roF0RzKTQRunHHh6OzthAp6H3xSZ0UhjmOr1XVoSQtFDai68vY8RukrwCsu1b0TdJ/24NTqFdF01R4kpyLrhWwhAVBbO+t5zFnz5H4twI9h9WcPqEg9aPdjHh7qlMvCNj4MlIEFD7qxEmpePInIGoUlG9Mx+/uos47r6POV9Io/CMkco/f9SjXLhXW0MQULz7Jv/8nxYqXtzaa8w6JlmNKWUKCp/+8yCmTIGJaQLNH+6mcHe1604Am42jW1oxdAyN1+Daz7TodDuau9ahUg/PzB9y8DPqGwTSl4R7JAg3EgQHc6WqpXJzLtmvnHLpdZcjjCZdGAkJIF80uHYQ3RhAzc3WpO+m0RS2KI2YZcMkrQuYatsQggLdf2FCAuq0RBau8/f6mEYj48bIGOayG33nJ+2SNtnu3X3uYrVaadFrV4XSUXLJ2xEailpm6ybffjVRqb60WzVYqgdvRIRnhGKuarquErGSViShCfMj9OHVBPhJC7x+6iKCZ6eQKJQTFu1aqEEmkxZGrU7OggWAIGAwQGteLfZ9B10ej5AQz5J/PsiEu6cSuHY+4vwFiCEh+PlJ5/ednEiTPAKnqXvMZN8+KDp6jQhVcDAKUzvR8nryP8nnwtsner3m9K/ORaEbOKRx880QefscZt8c1qth1dHm4OTxazRV5HKmBFSi0Q69cWA0SuJqi9fpBtV91WXsdmRqJdV3fZMZc0cmzOgpl78/y7lCmqu7PG0WY9+5L5ejeYvX+uI3LQkSEwe8zvFfbqG5YHCeWZMJZB3djRHd2kXIVMOnVmxp0KMM9SDWnZAA06bdECEagNGpHz2OS1w2RtTWDhoaIUFbDRcuSHKivaBQgDo2jObCJvzXSA/Iw4Jx1jUAgT2O9/MXcAaH0lTQRExSdI/n3SE6M4zQ976DILt+/I0xX1pHfbmZtvxauFNSzkxOhqD7p9BY0OxRbD0yEhISBdSdibTLLSgypwz8ossIwpWeoVnfXgJt00iVaxDVkrGQ9b/39docLCwMXnyumvuXnSHzOytRqgQQBKa/9A0ylWry3pORek+G+2/mKnx8YPU9fj0MkZZL0jfZpwVSyneRGjWPwLhLTVRkMoKX9Z2Y6E18fNxTdHU6oWPDHgp0s0jO9CMszL3r2dsMNC25mwe+Nbj7akS4JEykqK/GOlnycFitsPcLrzD92WWEL+pZ4mq3S/bHgoUCTLplwIocc6eDzn0nUT0x98pjTqsdY6sFXYSLuR52O52f7saXTrSGRrCESpPmMFVmXcbW2IbCk6zfiAhJmvcGYdwzMobx8YG77wah00DErDhpJRvgJg9IDcNQ2rXbUESH019vcW18V+LpYJApZGgChllJUBRxGNyTs3cLQcBvWhLm/O5lt0HpEUy80/PFe81jEcz+x+Nk/PnLnik6XiYwEKWf5oqIbF9dSgMDoVEVQ/0nhzj70jFEUXKSFFepOXsWNMZmKt/ah2izQ1MTYrtn3YGv/Wk6nZIxEhoKM2bJEFatQhXihW5ul6irg/feg5eft1CcP/hQY93ZBoxNUray0Gmg4IOzHH6tkKrTDW7nn9p9A1j73SnExQ16WMPPJWOks6ETe00D57IdnDlqIdhWR9gUaRt/7GcbKXjn9JWXyOVw112XIiou5IrU5jSg8lHgF9+1GOvPV3Hk8X+5PMySCgV1ewtQq6Flx6lhN0IuY2/Wown3wDMiCCM25pFg3BgZw4SEwLRpoJ2ZwfmolZKIyABNKIInhmKqaLziklfGhCNr6tsYCUiLxGq8FPAdIxn/V1P54hZvKM/3SfzaDGb+/gGvnlMXqEChFLyWu9DQcFWxVS/y8jK7lbgQI2ej1hB/WyaC5BghOlqSN/ksP426fYUIJiOG9Ttp+Nt7lL5xwLNW6VdfVwapqVIhRFoaPPCA+/1m+iMyEtatdjCx5Sghjr5/49fibGuX9HiuIff3m9nzt3M4HCCYjCT/v6dxFlwk599Hycl2797QaHNuN8UAALS8SURBVIUeiqJjhktZv62toC9q5OAhgdxt1cRN8kMIDEAUoTOnGF10V65DQEC/BS89aMqtQ5PYfXPlqKrFFOS6h0GjgfyWCAwGKIuYO/ALhgixtQ1tVOCIXX+sMG6MXAdMzZKTXRsh6VP0NoteReSUUEwtJuzt0g5PHR+BWt/QZ4XmtKfnMuOHq6U/zp3z5rCHBfn5sxx+tXDgAz1E7a9GFzm6sw8DAuCNN+C1/zgp+Pg8lpLqbs/LNCpmNW/DPyGIw2e0V2xOrVbazd76dBTKb3yZTQf8eet0Bq3yUBr2F2DRX8oXqK3F2GbtludsNkt9Fl0p6U1KgsMv5/HJ/+b32pqgP0pL6dcoCgiWs+S/l1JsiGDvT3dSd6a2/xNWV2N86W0O7rV3uyesbUbKYhcx5xuzpZyS8HDCohQEZiZQPu02pkx133BsrjJR+O+9tJZ7V7RvyLlkIDiVGsoSliKcOUVw3kHqnWE4auppKmlHYWgjcpZnPWxycqAtvxbdxCgKPzpHR43kiXPW1GJxwxgJCYFO33Dsvv5k3OP9BoQuYbfjbDfgEx04MtcfQ4wbI9cBGRlQ26rBoAySfNP9EBSpxqELkLpmApr4cHyNjRjaXdjl5uRAcbE3huwZlr7LTHtFEHA4QLHlc0rOD2G4ZpSjVsO990L2STvH3izkyFdfp3Rvl+CUXA5xC+KYlP8Ja2b2DMklpwjYUSCTQfDSqVhuvos5/3qqSytGrUb/m3/wyfNdC71GA50Gkdd+cpGdW2z92shaLdz0tYnMWe7rVvJoSbHI7v87zYmXc/o8RhRh53Yn55/fg58/RGQMEPYSBHTPfZk1tyi6lf2223247dlUmj/aw6lXsqUKaaWSyLsXsHKVgMKD7LuOi3XUvruX07/b2WuX4NGOfc58QuJ9EeRywjpKSKUIeUUptQeLUcVHuJTY3BsFR9swltRxtCScsr9vwNp2ScinphZrqOs5Nmo1iOER+K+YjcZ3OLKSe2Jv1mOxy/GLGt0bltHAuDFyHaDRSNGZMnPkgMaIIMDCd75xRa5dFhKEQiVgqnKhKZzNJjULGUAJdMhobKRtzxm37BGHA1RWAwV/2er2rvt6IioKbr1bRVNhC5qyAjTbP7viRQsJgemPTyP9t0+gig7tkduhVMLcubBuHdz/gEBmJlf6rgAQHEzwtDg68ispKuz6kBctFvDXWFFv+BAfbf9fWkyCgvhFrsibSjQ0wPsfCNTHzKA+enqf363ZDFkzZDzw8mpmfn8lgnoAOfbo6F713kNDIcLPSGd+BYWt4VIejiCQkgLz5l06qLPTLWPZWl6LISCatOduQaXx0lRsNiNarDidQx9V1S2fRWgoiGoNU6aA78x0SW9g4+eE+5vh5EmPzpuS/TG69homNh/FT2khOC1MypBtasIW6l4iqE9qNOmPzPRoHIPGaKSzug2rNgBf3fWTuD9UjBsj1wlTp0J+ayRibf/GCIDa76oJWSYj9ZePEZzkQkDXboeWFirfPTgy6SMyGR0fbqXwWJvLLzHqwpHJBSxxqVSWDL3E+GjmpptAm5GETa2jPij9igKmIADR0UTPih5IsqFP1PfdzgznKWzNXQJoCgUs/fpkFv75XgSZgM0Gublw/P1SDv3xKLYOz7sMV1XBQw/BD34At97ad78YrVYyJLySByiK1Kx6nJWPdX1OaWnStW02MO07zs6HXsbQ6JoXzmQUifvRF4hN1SCKcH5LBeb2QSTaOp00/vENjj/wR/7zp7ZB5/QMRGqaAl9fWHWbhsAQOaxahVOpRt/iJNTXDJM8C43IfTVYjXa0pmZkaROkz7OuDpvSB8HfvQTnhbcE4h/pxUQkd6itxfnxp2jlVmR7d4/MGMYQ48bIdcKECdCqjqQ1f2Bj5Fqi5saj8XehgdelIHrdwSKq8j2rqKBRSp41uNm/DQBBQLRYKfvLeixm16yhsO8/SVhWDAE+NhInjC09B28jCLD8yxMI/unXmPrtFd49uVrNzH89zaQF3UsRo6OlnBSQPCxhYVApT6Sq1EavsQ2nk5pt5yjbkt/v5WbMkEpFrzVCRBGyTznY/ccz3te08fVl/kJZt8TTK16kkhIO/2IbF/xns+Og1iXnYdTd88mcJwnjleaZaPj9a+R8901MdR7mkBgMBBprsHZYiM/bMuRl9MHBMGcOpEzWwNy5tMpCqG3VIAigu3WZx3Lv8kA/IiKg3BpFQWccdSer4KOPsMlURFa7JrJ2mdir0laqDpZx4KlX+z2+o6KVysOVngy7B02ycEyNBnQYsEaMxbKp4WXcGLlOUCggbnaklAsyQL8Qj1m2DKKjKQ6ezcGcrh2KKwrjVygpgZwctm3z4PoyGU4naOrKyH7xuEsviUzSEjAnDVN24VgsBvI66WsTmfzAVORqD5IcBvoAXUiciIiAe+4VuOW3i1FqezleJiNsdiIywbMvSxBgWkA5k5ItCHj/C++rKtW+5wCN9mBagqUW8K7kkIRHdk2/+TurkQtOAjJi0IR7qLhpMKBUQmhGGK3L7h5Ud11XCQ1Faj29ZAk1NfDpFg2OoFDOafrveN0fgbE6ghZPQW014DcpltQsHfaWdoTWVpzBoR47fFrOViHz699L0rwvl4JXj3h2gWvoEHXklWppIpTdFR6IDt1gjBsj1xEZ8/ypadHgqHW9jNEtJk/GmZiMrLyUwkKp75rTCXv3unEOmQz7xi1cOKF3v2mnTIbFJwiHXMWJ4mAa6l1bbEIXpuFTW9yjQ+uNyKDWp7w87IeO4Y3km/7kz5XBfsSv9VynRZaaTNRd8waUCfcGHY1mLm7IQ4iKxPqNZxH8dMx1s4q0owOoqmLa1xeR/swazz0aHR2g0RD7nQcJjRlGfQqdDjQaFAowOtScjV5LZIznCaNxE7WoHUY05jaW3KRE8PWhoQHOm1PINyVy0HVR4m50Flbim9a/h0KoqcYSGuPZBa4hIlLA4BNOeeRcZs4azxkZiHFj5DoiPkHAEhRJ5Qn3QzWu0h6aTEBzCWpLO8f2GNHrpTy1ASqKu5DJsP1/9s46PI7z6tv3LEorZmZmWZJlZuY4tmMKc9IkbdL2bfuW+xXT9i0laZjjkCF2EsfMbEuWbVmSZTEzr2Bpvj/GGMtidPa+rr0Srwae3Z2Z5zwHfqe5g/BLW9mzW+ydt8LWlsq7nsDOQUZIjIWkFNoDVF4uWLraUH709r17hgJRHJB5fPgID6d59wku//7TQc9HuJG2Nti9Gw4dgqIC6bw5OVCW34O64UHEYID9fz5JzT8+gORkXDyVjBnT++iEKML8J/2xXzGrf9aiVgsrV2Lj78SEAWz90lOUSmizdCRsUXCvJMwNHUYMuuvXk5CUiGVlPl5e4JJzHGxtsXMQyPScRVMThIf3YXCiiD6vBIfYLsqNRRF5eQk6196XJJ/42VZq0m9+7mo0YPDyw3J8XK8Ver+LmI2ROwhBgPifL8Jzdv+ku7uiw9WHcN9W3MVyprd8RU21iMEAp3oWNQGZDJ0O7BsKMJ08TXZ2L06uVjN5tgUuk0LRX8jquVKyIKCODaPp9ODpjfRwGOzd00sDbCQhl2O3bhEu980ffK+DKEJhIfrTaViqjCT619L2xoeU7kgH4Owfv6H4vd4lBZpM3LYp5I0UnG/CqO/e2CrK0RHRmoICA2mHm3FwoE9GgK0tyIP8+x9WiYjgag+CzsTj6uuliX+wUCjAxk7GtGm92y990yVSnn7r+hsqFWo7C/wDZTBnDsjlaKYkIXp44uZGl2JxpafLOPO77Te9ZzBAc3EDxpY23OK6qMZpakLUajG49K5ip7VRT9uJc1g63FrKbBw/iaSJPcjH6wxR5NSPPqOhtKcrvdGN2Ri5w3CLckZl17NusX06vrcS10QfZGXFWOZn0HpKmhxOn+5hqopSSbNfNIKnO/qo+F5XCctk4DwlAnl2Jq3ans/qoQ9PJv7Hc3p3skGgdd8JjhwafZoSV5GFBmMf6Dj4JxIE2gQNJzeX0qoVcQxxIukf67EbJy2LXe5fgHLxvF4d8syeBs688BHNdbe/UCtLDaT/8lPO/GFnt0ZjYICIbaATmd5z0Tu6kZAwzK1ELLu471taSDvexqG7/0lhag/K+PuAUgnz53dTufQtj5peDwW7svGY4HfT+xpHS5STkq+1QxBmz8LfX6oa7IrifZdvcdOWlsLut4vRO3uQX9JFEntpKR22rsgte2c8lJ4pR2Wvwcrz1orEkGj17VqFdYupupaW1GxJu+E7gNkYMdNrLCIDcWguoq0N1Hu+xkHehLMzPcsBiYzE9cGFJHhU0NHYRmQfnDhWsUE4KpooSul5R08rN2ssHbs30q72SxksnExVlLz6FRfOj1b3yNBh4ePC5D8tQmMrZYM6OQtEjpEmiunTpX42XXGjMVFbbeLcF/lkyGO5nNW5d0AU4fjHBZT4TqQ+YVb36rGiSP2kJYiz5zBppvpaD6ARSUEB6g/eRLS0ROM0OIsVF5fuq3mLPz7C3h9d91ycTTHh1piNz6xvzdiOjtzkYrGwwN8forvoGymK0JCah9uEwJvet7KCtsslVKm8pfyc26AvKKXVwQulsndRyJq0EjQhXp16tuLj++5EbM8vp8XKDSvb4RFsG2rMxoiZXiMEBuDWUUR7m0igdwdTmrfj7SX2rEutTCatIiJ8sS3NurlvTEdHz9wrKhXqqGDqjnZd/tkXZDJJ1600X8dN+uYDhMrbDY/yVC78dQeFBWaDpCuuPdtLS7n85kEuf5nV431Lctq5+L5UBmoywZdfy3CcNYbF/xvLmAmdrzTz80EeFsza30cxf6mq+wWphQUyZ0fuvntwo1ZarSR+vO3dOrJ6/hXcREdFParmWiaHVuOiLRjQ8V1Foeg+0iTPukijtZSTYTTC+e0lBPiLCL7fSiydO/cWT09srNTU8XaU5OmwqivGc/K3jJHmCmybShB8vEm8Qf/s3HtpXHjp4LV/Fx0v5VytN3l5cOJE15/jRpqySrGP6jzptT/Xha6wnDZ7j5uUgHuKaBLJ356Jvm2YBCr7gNkYMdN7PD2x1Miot/dHpRLQz13Ua2+CPDqCwI5Mysquv6drM2L68uvrS9ouDBP78eG0p/XxydwNbm7w/kdyKl7aOGAZp8XF0FbdgqW3I2o1RDSdxCV9/4Ace6TT1gbZ2ZLETJ/Ee93cCEp2ws23ZxUiLdVtnHrxABnbC6ipMtHWJsnhr1gB3ooKWi7kd7qfry8sWdK7hm4hIWAzcI2Gb6GxUapWO7S1HuUnHyDb+FmfpFUN1fXEx4N6yVz65I4cCGpqkNXV0OwRKhkiJ9twrsvGdVLIrbN2J4khnXmeKtIqMOmle7TgYCF2vnbInR1orOogf8clEEUstm/GpqWcaY7nkbdJAkeiCGV7M7G2u6JYp9PhaiijQu5FQ4P0u3aHyQStrUBxCW6JfevD0xWGojKMrr3LX7lKR3kd+X/dOGxi2X3BbIyY6T0yGWJwCNW2weDpiWtjNvUNvUy+Cw/HQ19ERV7rtbcMCgtyt5yD1Cutx/Pz4fJl6f+/ZZi4TwvDNta/R4mG3dH4LY2pgADoMMhJ211NwUtfDYiutoUFvP2OgMvFg8SPU9HUIqPNK3hUdkLuLZaW0NJo5Jsf72PjvV+QsrmXNd0KBbLYaGzjArrd1GiETdstaZ06n+CfrMDSSoaV1ZVS4uxsqt/4gpSN+Z1+7QqF9HP0RpBvsKU87Oxg0SJ4ZkEuEyPq8WzO6kW2+HWsdPUoJibfoF0/DGRk0O4djKi2YNs2qHh9G2MtziNzsLv1JuwBrU0GMn70NjUZVTQ2Qs2pPByTAhBFOPR2Dk2b94AgIFiocXYS8Qq3vVZTnpdjwqqmAN/pgZKF/N//Yq3W49Gai5uLqUfVL/n58PWnLdgJTTRZ97xnTo8QRYyl5Rjd+3bc1pwy2u3csLDug57QMGE2Rsz0CefF43BP9IKICBwrM6mr6+W8ameHRYAHrWevV7hYWskoqrak9M3tUtaZXg+bNkFtrSSWdtUwASwcLEn6+Tzkyv5fwjt33vws9PWVFmqtlk4IaWcx7j3Q73O4uIDc1opzJ9uoatGgiQ7g8taMzmez6p7nwowWEsbKmfjTqVhrTLj7Dl5yRUcHrF4N994rqbTeVGYbGorxsSeZ+puZN33tlZXSZfbqq/Dir7Uc3Xprs8DhRsjPw85ewHr5XHQefpi0vWz86OoqZZcOgRBap5w9S+Oxi1Q6R9HRIXl7OhraaCpuwngho/Pyn27I3pmPxskSm2A3Xn8dlCX5NDsHkpoKpqxswpeGShtaWhIcqUKYOePavhm7S/HwlCH3cpdWCo2NCIh4O7cTHduzZ4pSCRUppdQKzuSXD3CSaV0d+jYDMrcuSoe6oD2vDKO717D93H3BbIyY6RNekwMJmBUIERFYV+UjtrX3WuLdOikcMSPzmhEjCKCw0ZCTZaTu1c9o2ncaQ0UNpg2fSHf+xo2S0loP6E2DX6WhjQ0fidcSFtVqmDoVXMIc0WpBnnr6JkOoL2i1UiVAo5UX+Sn1WLTU4BB0m6qUgwchc+DzYW5iCHVCrhIcrmDqP5bjleg+aOfQaLouPvDwuDUi4OYGM2dCgEc7Mec+xC9l87B8P7fFZJLifKtWwfjxaD/9ikNrXmHHPzJpaup+d0AqkR0CEbirNJU2U7D7hntmzx7kNZUU78wg92I7DQ3SLe3jKyC/exm9TYwQRSjbfwmXyWFSye753Vi1VFIm92HXN0YmuuagjrlijGg0WMyefM0r0tICdWfycJ8UKH0ngiBdOFZW2MyfRFRUz8agUpikXBRvL5KTezX87ikvp9XaDY1N35JX9QWlUi+GUYTZGDHTPxwdkbs549N+mfr63u1qPyEC2+pc6iuuly2Irq60WjjyZeNUmtXOVOxJpzWnlEtvHEJsb4ePP5aSELpBr4cvv+yZQeIqr8Xi1CE+//x6isi0aZAwx4lsIZRqkyM9y869PQ0NkJYGlUpv5IKJAN0lwhJuo47l7w+ffQbHjg1eGMdggC++kNrfDiG2dsKQrc5vtCeMRroMBdjaiMz0usSMn47D5elVw+dB6IyGBinpJTISWltRVpVCczP2F49io+ihh6Qn+vQDyKWPUyn/4uT1N/R6rKyg1TuUJp0FHh4wfgJYzxonuSJ7SVmpiKrgEj6zwzAKCnyLj2JnK6LetY141zJcHI3gcyUp1t39JgGYtDQIluVhE3tDoqtGA9OnE52oxrGHletWR3biXJNFwgQ18voB9Ka1tUF5Oc3WHn1xGIHJhKm0HLmP2Rgx810jPBxfbWavk1gV7s5YJ0eir7teb9c8YxnaqGQSledQezqjbZNReySL4+3x5OaIiDW1koekm5WrtTXk5sLWrd0vcq38XQgo2I/h2ClOn5beEwSwmpKA21MruHysBmN+Ue8+3Lfw8pJyUeo03qQ7TSP/RBXth093mtFZYx+M0SDCrl2wffuAr9JFEVIuqDh02YOSn/+Xqre+RFfXl86FI5eGaj0Hf3cQbUUzJqPIkX+eIfMHr5J7rPKWbcvK4NM/5VHc4oDlhHicgh1GljHi6Ah+V3Q4cnORCSJNTgGE/W49gmbwNIX6Snuricb9KfivTLr2nqjXU1QMmjFhyOXw8MPgFOwotZLuAXVnCznx2+sNrTL3luHprEMV6o9RpkQQwMFFzjmPBcz0zZEWD1c9QWPHglKJKEpdo9NO6QixKIbAG4wRX19ISLimkSKaxG4XAgpRj79VNe4VaX0KM92WPXswpJ5H36jFoaUPTftqaujoALX36JJ9NRsjZvpPRARuTZdpqO5975ekP63ALep697GZC9SMeSCWpnMFWKn1ZChjqW+3wPHMLjIaPLmYq8YYHdejKhcvL0g/3cZXn2q7nM/tXNU4+NsRnL2dRNWF639QKkmeoqbGP4mc9472+rN9m5kzwSbUg4qoWVyyHUv1Bztgwwa+LWihcLbn4EVnMjOhrEqBqW1gZc8FQcqnaI1IJL3IlksbUjCVDV4Lgb7S2Ng3O6w4s4UDP/oK7ZlMCk9VknmikYu5Fhy0W4at2/XJW6eT8oW2/CED930baPzq8MhPKM7JQYyNw/6Ze3HwHHmGiCjCxS8uY2MNHtOuhElMJprqDBQWQVCYgpkzITQUmD27x+GZ1mNp1FabEEXJ61l1KAvXiSEgl9PUIkMUZJwQJjJ7jTPqwuyby2GutHbW6WDT5ybE/AIascNoe4NC3axZN7WArj9fzN4VryCaRE7+ZDNV6bd6EJX2VpLDdMqUgTVGLCzIO9dM++USLlS59T5CXFZGvaUHtvaja3ofXaM1MzJxc0PlZI0uM7ffh9JoIDBaQ4ejB42b9lDumUR2my9qmZ7TvitJl8WRvT2nRw8xb28wylUoN37M+dO3n9B9fSF2lgsWFlD+/m4oL7/2N7kc4p8YR8WxPJpy+hfSsLCA+QtluHsIlE1cgd4/GDEvH/bsuWnWtbeHwLXjOGo9j4K9uRiV/UyOy8vj22pPggDzFilwWD4dxQPrsYgeQV1F9XqorKRy30UupvbMENO2iFw+WEZLC+RWWuP1zHJC/v4kzuOD2ZdqT5VrNK2+4VS1X++Iq9VCeJCepXcrCPj7Mzh8b93I8oh8G1EEHx9U99zFxClyatPLqUmvIOWPOzHqhr/pkSjCkVfOU/H1GTwWJVz3TBiN5LV7oZmcRHic+np+RU8ncL0eU3oG+ohYLl6ElH8dwas5C6dJkhpvdTW0WLpQ5pFIa3kjVFR0GlZtaQHv4uP4FB3FMtgLeeMNrtxvaZq0pFzC4OJBW0UjrafS0bjdWr+tsNWgdrWj150Ru8PGBisruOwxlepGFf7+vdg3JQWysqhTumMnH13eztFT92Nm5CIIyKMi4FwW0JcuVtfJz+pAVKlxWjIBwx9/jGL2CnRtlbSUFRM9sYRS+7Esbn4NtPO67Ujm5QWhEXJkaR1EpH0MCes7NWLkcsDDHddxRi7mWeLt5nGTle4bZUPD+oWI8v7fLpGRUtt1cWkQF57zpqOwibBVgci+lVzov2osIS4iEQFRPW4IeDsKmhxxfPNlbOZNRJg44dp3IAiQ/Hg8esMIm4CrquDoUTzScqkLeQa4vb5Ie5vImfczaN62H0uhneBtP2T69OufJy0NmppgxgyYOPHmn9/BARwclBAcOnifZSARBEhK4upHKNuVTt2OU9fLv4aZlhZo3bobK10z1TnWeGvbkFlZom000JBbS8yzd2FpeT2Vo8dkZ6MVrFH5e9LQAM17UrAz1VP6+TG8AwPIz7eiJGwJwQ61RJ/aJtVDFxff0lFPqwWZaCTWrhDvRgFax3O7BJGO9GyEiOlUHs7G5O2LtUsnXiiNRnJ39kWVrCusrbHydqDMmMjY2F4evqkJsrKwyxawN0YBXbTHHmEM/xVs5o7Afmosnsn9F/7xubiDzzYYqHaLod2oZMqlt8DPD5UKgupPEz3DhbM1Pogpqd0ey8sL7rkHrAJcKTxYwE0Zqt9myhS8nlmOTUU2ucdv9YDEPpiAXUD/e7IIglS94e4lJ/lf6znvNpu0P32DqLs1xDV1moCDn20nR+kdbmH27K+K4tSf95Hz/Ms0nbxeqSPIhJEnY37lh7P5n6fwi+r6YWphKTD58Ugmvf4Avs+vuCnMYjJJoZ7nnpMSkgd6zrgdomkImiGKIq0pmYg6PcbyKirOlne/zyBTVyui0mtRKCAw2RmZlSWmxmYubzqPyscN5+g+VlGdP0+5cwz2DgKtrSAgYmUFnsvHYVBbkZMDUfO8WbJUQNnaKCX8dmKcabXg4aMgIABITJRcp51+kDp05XVYRAXTeDobTfxtjFVf3+6b5fQFa2tsls5AppSTkNC7XUWNFUYjVNqGYBXp1/0OIwizMWJmQHCIcCf6waTuN+wGZWsj0+q/4PBRGRU2ISgqSpjhkYWltQxD5mUmBVeS4zCW8i/PdJtQoFBIXo/oGS5UVEBLfnWnJbrt7YBajdzBFofp8RRvONTvz9ET7LxtWPqrMVivXYKgvNXrMlARA0tLGPvCFNp0csqyW1AHdi5dPeKwt+/ZlyAI2HrZEDgrAEF+/ZEmk0lGyGAqpH4bo0Hk2J8OUpndexGv3qArraa9rA6DmxdxLz+O19jhr5xoKGtFhomQ5dE4LJoIwNnfbqPxm6N4zQzrURXcLbS2Qk4OxQ6x2NlJ/7SwEAlfFoYsPpaiIkk+Zd48kMmvXCsxMVeSUm5GpYLpsxUI1lZdJ85eukSlhR8uLtCelY/zxNsYIw4Og+ORcndHHhdNYqJUCNQbWmXWZGYJ5AXOJj19ZFWod4fZGDEzsnB0JLg9ncC8PZS5J6Bt0GE/JYaOpMm0tQsUbT5D0r3hXMoS0aVn9+iQ9mFuqKZPJDej4+YM+it36sWLUHSlWCbw/snILmVRfmFohK8sNQKhi0IGPVfBM9Ie13um4/+3Z1C79N/bYuZWtFrY+seL6HcfoOzlLX3UvgdEkYqvztBSePvuupUHs2iPiGf8aw/h5D+E1lYXNJW1EDzZHbfHl4EgYDJB1aV6xIYmqveeR2fo5XSTng7HjpHV6EGl3pHWVsnTFT/OAvWKxSAI+Plxs/fAygoWLOj0cEFBSIqk8+Z12eHYlJVNgToMm+o86k32eMc733bbQcHCAmQyZs7s/a4aFyuyLePQWrlSXj4ionc9ZhQN1cydiije0JPO0REnJ4hsOIbeL4iOZ3+EJuc8wavGIMNEzZ40IiNE2qMSyfrgdM9OEB5O9PNzKNXaU/n1mevvG41w4AAKucimTdLCzdLDHusJMRR81P/qmUGnl31zIh6bjE+Mff/OqdXetMLt1XwrinDmDGzbRs3b2zAVlfRvLCMIUYSCi1om1G8nZroTQYsjEA19TCrNz6fqve2cfOxNcjI6b9Zo9PJlxj+WYW0/ctL+IsJMeL2w+lo8TKsFZXszJpUF3j9ag8qmZ72FrlFdDUeO0FTWgqYwkyNHJIeG/Zr519xd8hs1wQRBMkS6Soz19+8ytCK2tdORXUi1Yxi69GzEkNCu7JZBpdtGjZ0g2NvRPn46MPB5tYPNyLmSzXxnEQTYu1dKFYhxcETu40mMbTs2iyeyeYtAjOICoXaVFIdE4Zbkg1wlJ+nxBLJ+n4dJZ0Cm6uYyFgSsbcDp7mkUbtiG66KxCCql9NDMycHB0EpjwwK+/FJg1SqIeGbWTe7+Ecv+/VLcuhOXdGcIsr57X7Kz4cIF6NCq8TrwEWJbOx7J3ggxMTTY+jJ2bA+cO4JAW/gYUne30r73KKEhsfj0Xu9qRCIIEKXMhu/dLS3B++HpMhw6RkOtCVtrHW7V6cCtiQP+0/37PthBwjnm5qZuzXV6VOUFaJ64D49op94f8ErJu4WHA7XWYcxOvprmcZseRR4enXfTu5FuFM3KD+dQVumMMciOikPZ2Cxf2ftxDyf29jgFgY9a+jpGE6PgiWvmu8CYMbB5M7x/0I+KBQ+hlhsIE7OIjhHY3TIe8dgxfFYk01ajBcAl0IbJbz3UvSFy4zlWh9JgsqVgc8r1N319sc44RfilrWReNJGaClZu1micB1A3YLCIjqbupQ20vvUxvZa/7SWhoVIL97omBYc819DcDLqNX+K2bwOFL33Jrj+eobWuvctjlJXBhQw5mvlTcfrpY6hDR1eCXbeMGSOVlPYn5FZVRf3pHDThvsS/+iQ203qZwTiCqLtUhcko4jnBv1f7mUyQf6hYMkasrDAuuxuFStZ9Mqda3b/v/uRJbIsukNPiTtGhAirKjFRb+lJ7+2jZiMTNjYGXpx8CzMaImRGBuzuEhUF+hSWvva0kw24CHD3KvLkiJY5xFKa3EBqtIvn3S6/tc+Nzx2jsXtlcpRbwXDuN0k+OYGy/Ur3i44NcDgFN54gq3YWH+wgXvboRd3fUMaGkfnyJwv95GeOxk4Mq2hUSAk89BXMWqzkedC92z9yHZtkcYgypyFLP0Grswg3f1ITLvk9p/8d/qfnDazg6gqvbCCsp7oS2Jj0VmYNr6N3E2bMoli4k8cXVKNyHOFdhgGk8cgH5tMm9rrI7trmCihffx9DYAsuX4xxgQ1xcl2keA0N+PlbFl/ApO8H8otdQ2VvBxYs9locfKfj7SxICow2zMWJmxDB1qpRwpVBIUuzU1qIqL+SuVUqO6sbSuOP4zTukpFybfLVa2Lev+3NELg/DYGFNyaE86Q0fHzTejiQmyyl1T8QkjvwJ8kas5k/B2Rlyc0S+SPFBpx/E8ZeWIi/MY/yYDvyjrGhLmIRyXCJujy5l+p/m4ezSxbltbVGuvpvEVYE4qFtx9BzgLqeDQGleB4ef+JBLf92GaByisoSpU3FwVVL40pcc+95Hkiz5KKS9vg3DyVT8H5jeq/0yM6Fiy3Ei1sShmDIRgoNxde1d/kNNSiFFR/sgo460wGn3CMTezQKNvpFJ94yuzrcgFaHdlEszSjAbI2Z6jL73au+9wssLFi6Ukt0/3qymLjAJjh7Fywv8ViWTtbMQfckNvUWKiuCbb0AUaW6GrCwo6SYnUiYXmPjWI/jNDZPesLZG+fB9KJITmNy6iwsXut6/O2pqGFq3ro8P7mtnUB8/gzF+dYOrGeLmBkePwp//TMSh1zj7ZgpGIzjMHIMyxP/W7UURzp2DI0fgxAlM5y5gtXQWCf95CGv3kSvGJIpw8mA7Z1/4AE11IarWBtqrm7vfsQ8YUs5RltN6/Q2Vivz3DlG8O4uQYBGhZXDOO6hUVHDpvRMI3l54T+x5UlB1NWz/pImpjunYL5ggNXNCir649KLNSvUne8k/3MfkaEdHDInJODuDZsks3CL7kOtipk+YjREz3VMpGQA98Tz0l6Qk6TVxInyQPY7Wi/lQVcWkuVY0+cdyefMN1oK3N5w6BV99RUuztILcu7f7SIXK6lvqVw4OMH06/opiSg9c7ldtvoMDfPiugdSd1UPW5sR+6VTm/34ygUujB/dECgWsXg0+PrgYyvEIsablquJ0Z8tHQYDwcDpKqsl7ZQfn3zwFCgUyR3sprtbSgrGyBm3RyArKiyLEu5Sy6MVpTN7yQyZ8/ByW7nYDf6KWFire3k7Wk//kwtdFiCKceO0cZRfriRtngeukkG5Vhkciho8/p2HHcQKWxSIYeraC6eiATz+FGZqTOI8LouhCY9+8QhUV6IvKUY+L7/2+ggDLlpE8UYkywJv4J0ZZOcoox1xNY6Z7du+GuXNJSXElJORmqY7BYsoUaGuzYc/nsczZewzLtXcx+ffzsbC5wZC4qqCYkoL8khFBXEp+voy8PKmgoVdoNDjcNR3/v+4iPyeQoNC++TnlcoiKU1Dwyk7KTkQw5fsJ2NkPsp9XEIZuzlKpYP16wqLPE54U0u1yxiBXkxawnLZxoajkRkQROuq0XHppN4YzabS0gOu62UQ8Nnloxn8DHQ1t1J0txGPGzbLhMhmoI3t7AfUe4849FOd0oFFA2uY8Lms9cdxzhISHkrBdNmNUGiJ0dFB2oRZrJXi3ZIEstsvN29ul3OuDB8FB00F8cwq5NTGUb9uO9+Sne18Bdvo0RbbRRPj2IcFk7Fjw88OhNROrHyxDpTGv1YcS87dtpns0GvjwQ1TtTWzbdkuT2UFBEGDuXFBMncj5DRfoqG5CY6+6rrIIUthAowG5nPbASEJCICKi74qbsnFj8fQQKf4ipfuNuyAxEapdIrHe/yXnf7WR9oauq0y6IyNjhDWTVasRksf2SFFJoZDi/dO/F8XEJ2MRBLBwsiLyf+9C/ezj4O+HMnhgq2pEk4g2qwgKCm67TUdGLmmPv0LO375AW9u/36dPlJRQsycN13hPLB5aS673NPLO1OH/k9XYrls8Kg2R5mbQFlRTXAyeE/0RVq3sNnnhwgX48EPQpWWwwu8MODhQciAHz9VTkCk6v75O/mQzZac6CcO0t2M4e55Ldsm4uvbhA1xdZYWGovLqRVzIzIBgNkbMdI+jIzQ1EX3uI1pq2tmzZ2hOKwgw/15nbJ9Yh8q+k1JbmQzWroVx44hqPsGYBIG6Ovr2IAKQy3FaNw8rY1O/xu3gALYTolBZK7EvvYj6vdf7VXpbXg6ffCJJYfeK1tYb1ORGFkolRM/1ZNrbDxIwaWCkzNu1RnLe3M/ZsY+Tve43pPzj0K1GnCjSfiKNE38+QLnOiWYHXxqqhvg7EkW4cAHn76/H/ZePsSM/DAQBpwhXjM5uI8vw7AXFxbDltSo6nDyxfWJtt82ArmrgabVgX3Se9q/3UHqxAUtjy21DjtVnS2hNzeq8T1RaGs2WbhhcPLDuT0rSaMz+vAMwh2nMdI+TlMRlRQuuVenY2CTR0SEllg02MhlELO7CZe7jA87OCP/+N17tuVRXB6PX970pmtvkENwmh/Rt5xuYuUCNvTqClI+yuFjnQbS9fZ+PFRuh5+XDSl59FVaulHTOeoRaDe+/L3mQkpI6t9IMBsjJkZIFh+IH/TaCgFw1AA//1lbUu3ah3neclkYDTVYeeHp5IppEhBu9aYJAiXM8Xr+KJ8ljGB0Q8+cjFwT2bpMSt6dOBb9RLrtSXS0ZFseD7sWjUk3EFXuho13k5P/byZjHk7Hxu25ElJVJ6WguLjDNoh6bVhMlO7Jwfv5pZMrOr4nCj45gMSkRK5dvLU5EEU6fptJ3Kq6tg95dwcwgYPaMmOkeR0eYNo2k6A7UceFYWQ3PvHVbLC1h6lRsju9CrTRdzbcdVtzcQD0piZA/P0LlqULyN/Y99ONi0cyU0k8wlVXw+efdVwxdQy5HO20huhMpiC+/Am+/LdVO3ohCIQXuX3wRPvgATp6Uup6ONjQa6qbexUexf+HAujcoXP0TGsfO7nRWCg6WXsNmiAgCCAJ6vWQj3nff6DdEQDJGyt3HsHClhogI6T2jEb75VzZWuedvERJMSYHx4+Hxx0TsTPWUV8po9IwgcMWYTo+vLaimJS2HoHsn3PyHqirIy6OmuI0cdRRubgNT+ZfzWSoNxV1XM4kinNuSR3vl4DZG/C5g9oyY6R5PT/DywrKsjITqk1y4NIvExBv+bjQOv2tz7FiEU6eINqRRXp5w2+7gQ4qvLy6A7/MrKPzrBmzCvW6RzO6W6mpwdsYryh6rHa9SWxeDs2wG0DMlJoWXG/tMM7A6vgd1agkmjSXjwm+eo7Uh8VQ4V6E+eAz9nlxUMXl4Pbeie2ntAaKiQsqL8XY34GXThJVP71WmOjqkSqrkZAgPV+DhYTfiV8dKpXRr3SlUV8OcuQJjrtgSoghbNxtxS91JzHMzkFtd15YRRUmw1scHWqu0tJc0cLnKE597JnSqqlxcDI0fHsUUHYtr8LcaPZ49C+fOUWnhx8VjjYiOTv0W/hLrGyh/82ssop7DvovtDh80YXp7CzqfJVi4DULF1XcIs2fETPdcfapPmkRA7WkKsztuXnkUF0Nm5vC2q1YoYPZsQkr2U1E0svIkQuYGYLtoCvmbUnu/c0sLvPYavuM8iBunxrv+Aln/+z5iRc/cP2o1zPn1RGwifbhsm4SmMPOWSdrKCsRZs8k0hpJTpqFObzNkhgjl5bjv20Dgtn9S+vQf2P+zXbT3IZ9UoYB77oGZM6UJfqQbIncaJhOEh8OkSdf7N+7dC/qjp0gcr0A1IfGm7QVBMkQAarJqSL8AipZGbBwUnfa937elkdoDFxAmTbxeTn6V5mZobcW+pQSjXIWdHdc8M32lYc8ZahxC8Ai/vYFx5gxkbcsmMUnANiG4fyc0Y/aMmOkFfn5Y+TgRmJFKXt4Ewq7ohuHqCn//O5mRq/CfHz587u/ISKw8jyMePQYrpg/TIDpnzHNT+rZjQADY2qLZuQU62onwFzl+2Yq0cwJj3Ht2CLlSRtwfV6PPsiYmsfPsyOBQGYGvrCBzazbe8wdZr+RGPDxgyRL8XU4gtJ2mNcSmT91Kh9sxdwuiKOXj9DV5aRQyfbr03127wNZCx7njBp60OYjF0lVdVl7V1ZjokGvAAK1obt22uhrr82eocghDp3O+tSlvczMoFBhWrEa324Zp0/ppjBoMNB9MheSVt1xXoigdOyND+pyP+6VgE5fQo8qy0YCuRYfKeogWIt/izvgGzQwNgoAweRJxrce5lHFDe3SNBmxssN/zOd/881Lv2soP8PhsV83Dy2uYzt8Fgkzoe9fcOXNAJsMoUyL38ybsnjjq/vEudYU9V+cUbKylzrpdjEFmqSZqTcyA6KIUFEDjDWF0o7GL8mQbG5gzB79/Pk/ouqR+n7u3GI1QWAiH9+ow1A5M7F88foLTr5ymPmsEJDANATKZNEk3NsLp05D/1j5WyL9AE+7brehPc141AN5PLsZ/wa0uDeP7H2Gfl4opPJKVdxlunfebmmDJEqzDvXFz679XhPR0qrUanBL9ydude1MrgFOnpHzvLVtg1dxGnJvyuBaXGuXoW/UcW/F36nLqhuX8Zs+Imd4RHo6Lxx5OHk5HvCvu+grE0xOL3Awc9m1ir/M65j7uPyyucptIHxIjfYb+xIOJiwskJiKUVXBuXy0O348l6lfBOPiMXEl1a2t46y24/35wdoa2Nqkrc3u7VJzl6Cj9NzJSCrEAYGmJfNC7oUm0t0saFzk5kJ8PqtpyEvI3cWF6XN+9WFcQM7O4/PIutKUil0zzGB/uNkCjHvmcOCFFWZya8pHlVCI6eSHU10v17rehrbgGv/tmEbw68dY/trbSUdmApQKWBGWgtvxWIogoSu2k4+KwM0jemX49d0QR8eQpLlol45VXTPmWz/GZ+AJKKxXt7ZIKtU4HixdDSFOqZGjZ3Rm5IsV7s8HaGofA2/9Wg4nZGDHTO2Qy7BdOxP2PRykticXb58qd7+GByquaxhJbzpf7Y3UUJg+9qOady/TpyAQBjSyFnF+9z5h3nuu7p2Ww0Ovh0CGor8dJkBFwXs6+n1gw5dcz8fBVsmZiEcdeSaOmUEuTvhV7dx3CH1aDy9C3RbWwkCJg7W0ilmknsE3dg5WFEduC8yBO7vuMVl5O24ebcHYS8QtWok42Xfft3+G0tUkVMuH+7UzvqMJSI4cpkzo1RHStBlQaBaIIXtOCCVse2vlBa2vR6yFigT+ae+/uPBwybRogGbXh4bf+uVeUltJSUEOBXRy2u7YQviIRpZUUtjh16rrgY2mRkTG5Z5EtWdTPE44cqg9cxHp89LA9V8xhGjM3kZkJxqraTpPIriJPiMPTTkvRvpzrb8bFoXriIRzbSnBoyMfBoctDmOktVlag0RD0wBSi//YgTl4jsOutUikJZmg0CBfOE6o9i6apgla9lDehCvZlytMxBLs149xWTEdRJTUVwxXTA2cnkSk2adw1oZKxTyXisHgSAUui6VMGLUjhgh070ExOwPG5e1H/8idSRud3wBAByEg3cffdsHpSCZZWclizptOSlo42E0ceeYeCb6Qy86i7w27/HdXWYhvihsNTa25woV2nPq+ey1szrv2731/16dOUusTTVt1CsHgZr7ul/jQ6neT1cXaG+1a14/3O/6OjWQchPdckynzrGKWnSvs5wMHBoO2g40I2nnOihm0MZs+ImZvQauGLb1pY6nkA5T3LO1+JKJVYzRxH9d6j8MCVm9HWFjUQ88QkFF/soanxUWQjbeV+B6BQgHtsXyVmhwClUmq9HBaGzwdbCV0cj/KGlAF5cABxLz1G7raLBKmKEaKHUXZbEKR4/5gx2AB97CJwHUtLePDB74zxcSONxU00//EdQv7zEEJhJaxff63r7lU6OiQ77/QrZ7CVt+I7M7j7r8pgQLh3PVhYUJ5SRtXxXOKeuR5Gy3plHzILFSzvZ9J1Q4PU/fvERQ7ZPoFX8QkC10eBrVRGfOGCZFeOHydSs+UUzRWlqKeu63HiqtjaRs3G/WiiH+nfOAeJ0n2X0Ns64hE3fM8WszFi5iYCA+GbL9zx23eBKJMMyzXLOr3hvJePxSb51kwxp0XjCTp6it1fZjFufMSdkmRuprcEBWH706ehpQXDvoMUXWjCqG2H9nZMMgUBP7wbwTrqzpq4v0OVMzdiMoqc+91WrMJ9sPW2BedEOiuJungRTu1tJurwXqL/vAqZugffV4JUqSKaRLL/vQO7mOvywxWpZXScv0TCO8/2/0OUlMD27ZwvduBEWRP3ytPoSHiYq4U7sbFXft62dsRX/ou1szOyhPgeh+Aqd5yl2coD76QelsANJbm5UogmOWpYb0fzVGHmJhwcwNpJTZXRiXPvn6Ppw22dlkGo7CxxiexkVatS4bpiKl6X9nH50nc7TlNQwPBVFo0ELCzA2RlF0hhcHAxoT12k9FAuFWfLpTj8nWSIfIc59+ZphNoa4n62UHrjNrXZZ8+C4+mdNLgEU+vQQ12OK6uZzM2ZCHW1RD0peUVEk0jOf3djO2ecZAD1l6YmaG2ltaSOkOazaEK8cIi8LlB4zc5MTUVXWY+Nr6NU29sTTCbqd53GYmryyCtBB0xff0P7+WwCbWu4VcRl6DAbI6OQS5cGr4urIEjekXZHT+zswFpXJ0lk9gJ5ciJ+3gYubzw3OIMcJZhM8K9/ipw6ZvhuGyW2ttjcv5y4/zxK0DRvnOYm9ipJrqNDEphqyKuTsghBiifeQYzG66O6SqTsfA0NG/cQ+j93obK9fR5TbY1Iy7lc3FsuE/n8/GuCZz2hvcVA+Qe78b5/JkprqQ9F0f5cDCUVRDw2MFnylZebaGyEfer5xNoWEPnIhFs3EkXadh+mxsIbh1AXuOuuHhnU4uUcqsoNeM/pb83x4FBfpUcmiDj7W9O/DoP9wxymGYXk5Umx16RBkmRISACNpT/ffOKAZ3k6dr1tgyuX47l+Bnm/3Ut1eQwuHt/NyywwELx9BLJePUD25w6E3hNPwlh5Z3l43wkEH298fvMI3k0900cpK4OU0yaqd6biXngSjVU1HchgfRzFp8oJnGs/uAMeIgryTJxPlxHtVk3guNHTuv7EX49gU5aL14IE3MYH3H5DvZ6C948xsf4cUT+eiSa+Z9k5VxPgz756Eit7FQF3S3oeokmk8K09ON01BUuHgUnkLs1qJqc8Fkc3FYF2amyTOqnuKSqiMbsKfH1R3be6xw26GnafpsQ1kUkhI9AtAlSWGbAJcUOYPWtYx2H2jIxC1GrYsYNBawjn4wNOcxLwXDed9AwZppSzvT6GZmw0rr4WXPro9CCMcPQwdy5UeCfhmbYd2w9fQZZ5cfDcWqMBQUCw69qtLoqQni55wdMzZBS5JHIxchXN42ZjFyUtqR0jR2DsvQ+kHGjmyG/20LBxD+W/ex1tSf3QnFgUyXz1IBVpFd9+G12b8TY73YxDxhFkNVUUWYZ16dkRC4vwydlPUngLGk/7Hg+xvBx2bdHStvMQIc/MQ5BL09XlzRcwtbYR8UByj4/VHQWtrsh1rYSU7MdjYULnrqrjxylWBcGqVZL2T0+oq6PuTB7W0xJH3CJEp5NE6qorRWwfXNFptdJQYjZGRiG2dQUYDPD559IFNSgIAlOmycjzn0nJRwd73wZTJsNj/Sw69hymraFjcMY4CnBwgMRZ9lhOS6Yqs5baVz+HPXu+2wZJNwgCREdLhSk//Sk886zAvPtc8Vg1GZ//vRcAK/vRnSxqNMJX20wU/2Mj3kXHcKrNhkcfQ+M1NIJT5RuPUvbFKQTV9e+xvR32vJjK2R991OPr09lLxYxZsi7nMSE/D1dXENQqSW23J4giRRkt1G3aT5ubP1XWgaDTYUg5R/lH+/BYOwOFxcBMno2NcMF+Cl4WdSyc2IB9bsqtz7vaWoxZlzniuhyfuT0Pt4inTpMtCyckod+1WgNOezu89qrIZZ+Z1Ctdh/2RNMJsNTM9wSnjELYtFohOPmRnSw/uwUCphPEPRXDxp0dwPnAKzZxJvdrfbXIIHT9ePmy9DkYKU6aALnYqLQ1nyUrT0hLaRsDsYRiIyQT790tJGD4+4OsrlS4OdSKp0SjlfNjYdHtuQZC0HZydpX9fmyN66CIfqVRUQEz1PuwDC1GpQOWvQD7bEgbzpzAYQK+nLTWTnHcO4/T9B3GLdAKgtBR2v5pLXNY3hP56XZe/i8kgxU+8kz0J/tEqBPtuFEhzcyW53Xvv7VKJ9SaampB/8gnuFdXUrHqKoCAoPl2B8M4W1CY1IbGWAyYml5cniaWNpQG5xlIqS76xAc6ZM4jlFVQ6RSLYe167FruktRUqKmg5cpYcx7XMGoF99IxGaZitbonE6Yc/n9xsjIxCrNxtWZX5EV/XP0xUVA/zOUpKMMjVXKpzIaoXujYhoQLZ02eR+95GYqZ0XrJ3WwQB31k9FwW6U1GpQOZgyT7nhdTOdcHmP89QeCENvz8/Tc+ebP2nrg6+/lpGU+1UIlI/xK7+FNbWEDLFHdn6tYMraV1RIRlBDQ0Y6ptpqmilxDUB/2eXYHtnKGn3Gi9tNtSdhTnJEBMD3t6DPhuYzp4jf2c2zefyaFy4noixHoginDhi4OTXNSyr/wz/ny9GiO4i/wNoyigBwP/n6xG6k+/XaqVVzf33c2uHuy7GWlhMR0E5bq5ypoWcR66czqktpbjmg2+wiEFpiWogvi9RpHnLXuauDEWeI0hCbU5ON2+TkkLxyXKKrCKInNqI0WjXfUSjoQE+/JDqSiWhwfWolL4MrqXZe4xGQBAIDh68/MPeYA7TjEJcI5zwcmwn7NQHFF9o6NlOdnYoPnyXw5urKSnp3fmmPBBIQbsbZRuP9XqsvcLYs1j1aEShgOnPxVKr8mDPuJ9Ts+UIGQt+iOmzz29O/jGZ4OBBSo/kYzQMnN/U0RFWrwa/YCVHfddRiheNjVB4sYXm8/mDGzZyd0dcsJBCgxenDrVz/jzU7k2j6fSlwTvnSEYUJUXdH/5QEojz8Rn8ZanJRO3WIxTvuUSJ4EPcdAc+/BA2v1ZN5Xs7eEC5gYB1ExHi47o9lH3gFfn+nuQYGI29NkQA6s8VSU3vVkYhnzmNDp2AsbgMHSrORt2LzN+3+4P0AG3qJTpOnEWua5OqY/z8bt2ooYH2dshrdOJ0th1lZT04cHMzdTUmqisM+MY5DL/boROMRkmnb9mykTE8szEyGnFyQiYDNw8ZOYfLe7aPjQ3IZMSnvcvWN6poaOj56WztBDzvm03hpycwNAxiHXpZGRw7BqJ4R0rJ29pKuW+tYQlcTlqLqayc6i+O3extkskgNBTLTR9wcNVLpL9+DF1D64CcX6WSGnzdc5+avIn34jwpjHTv+Rz7w36yBznRWLC3w+/ZpYz/4HuEr4xGv/5BXCaMQN/1UCAI4OU14G3n9a1d5HWlp1OdXY9epqLaKZz3NttIz4Djx5nndAYHD4ued5/9VvmnaDCS9uIuWqo6uU5tbfskBmddX0zImkRkKyQV6PJysNTW0LzsXhY/7TswuZZGI1Uf7aZjwnRs4wIlD9W3aW+Htjaa/aLJC5hFQoIU3eyWpiYyMiDNcxE5er/By+3rB0aj9DzoaRrPYGM2RkYjLi6wahVe9loulDv3XKPAywsbmZaQY++x5bWqa02fesKYJd5oXQPIfP1Qn4bcI7y9pQYQn33GuZPt1NYO3qmGCz8/WLAAfF9YSdW4paSbImh4e/PN/VA8PHBcPh03RS01G3bx9XM7ObTP0KvfqyvCwuDRZy3xeX4lS34WzZRPn8F32dC0QZe5OOH+zErmPuyN2socJR4oLn2cyrF7X8HQ3snDQBTR7z/MGW04xbUarMJ9MJhk2MpaiDaek54fdnZ9biaV/cpuak/lDFhCKTod6vAAhCWLry3Zy4oMmOYvHDhDBODsWUpLwWtJwu0Npvp68PGhauJd2DsIzOpp9WtTE0Ue4yj3SMDZWVoIjDRcXelVyH6wMRsjoxEXF4iKwnZyLEHlR8jO7uF+np4orVW0WbugsrPs1WQvk0HEM7OoT83HpB+kcMrVMorMTLy+fp3P/lNJXd3gnGo4SUqCsTNtmPbuQ8gfeYgDx9Xk/PwdTI036G9MnkzgVG+Mllaoq0vQVdYP6APN2hqUGukBrLFTYmHTi9VrY6P0kG5slBQb29p6X9Zl7hPQb0yV1YgGIxf+uZey93bh//1lnRoEhspaNtbOQFZdRdRCf3BzY80a+P6EU4TFWWDz0EpYtw7s7Xs9hoaD5yj7Oo3gn6/BwnaALlC5HObMuSl2YOOgYNGTPgNniHR00PLlfi64zSYypgv9D+FKHolCwdKlvTAqXF25HDgPf38YP34gBjzwjLRS4xE2HDO9QZgymahtr5B6bDqRkT3IUg8NRf1UGOM/fJPNZS24ufXOP+c1xhWPj55GJh/EAGN0NBw7hr2pDlVxLu++7cJDj8hun4RvNF6f2EZC4LMHCMKVhZjSiulzoCR0Ned+/yU1T7xF5J/vx9bfEWQyLNctx86nDd2FS3S8+ybnhOXEr+lvj/S+I4rQ3AzVl02YNm3BkFeETietrhRzZlxr5W6mD/SyMqSjzUTOn77AIMqpK2gi8m+P4HZD00GDQcodNWbnsvWIEwEXdpPwXADWa5cwTi5IZUklJnjmGSlxoA+YyirI+edXyO5Zjd8Yx17ta2jTo9fqsHS2uvWPnWimdxZB6RfHj1PU4ojLlPCuC7PcJT2b+Hjw8Ohiu29hioxGZSH0VKTVDGbPyOjG0RHnKRHoDxyltSdpBe7u+CW74bpoLEH5e7h4sfenHFRDBKQ7PiwMVZAPDtTT1CLjvfeg6UIhzU2dJFkeOCCpIx05Is2UoxBvPzlzXlqGfNI4VHY3TAxOToxZ4k3i/8wi4n+W0vTuZi5+kMqAxWt6SUcHnD8P2w47sEH1IMetZtPQLOdsmsC5lw5z7qcfd52E3NEhJeteugQnT0Jz87BrGwwbBgM0NSFqW7n4+y2cf+14r3ZPfe001WmltF0qIul743CLurkq65tvYOeWVs794nMmZr7FlIeCsV2/5Pr9q1DA7Nl9M0QaGwEo+r+NFPhNY+L9vc/9yf7XN5z61Ve9P/dA0NyMePQYRzVziI27/jwzGUwYOzqPeffGEAEwmgQWLOiTs+k7i9kzMsqxWTiF4C9eJ/PkVBJn9KxhlDB1CuHb/sXRbbnExAQNruVuMvXOJS8IsGIFaLUE7X6VFl0Q/gnh2DYUceHTExgXLiF+4g2Z+f7+8Oab0tPi8GFYtEhqsTnKliMqtcDYZ2/thyGXSy/3WVEoPZyxcLKi4/ApFCUFyCNCpQSQIXriWVjA5MkwcSJkZck4eXIy1dpgJhgOUxExA4qLO13VotNJRuOJE2AyYTJBtVZDqqOCsasCcA7t3ap61COKNH/wBc1aGXWncyg0+jD21z0P3ldcaqT1y70Igpxqz2haXAKwueF6T0uDlBQIzjlEkFc7vl4d4GR/80H6cX8Yt2wDVyfSqr0JeH5SryNurSfOU3kgk8AXn+zzGPrEFctXPHCQarsg6pW+BAVd/3Pup2coP3SZqa+t7/epFAqI674wycwNmI2R0Y6rK/ZJweRsOw4z5vVsH0tL3FdOwf5feyguCsTXb+An7rY2Kb4q1+skjYk5c3oepFSpQKXC/9nF+Hy5lXf2epL0dDy+X+zn5G+K2bviLqY9EiwdLjAQvZU9yuJiOlLTUdXWISQmSGnitgPQzXME4RTpBoDeYTJHfliB7ZZvsLf/BqtwH+weXYXaZWg+r0wGkZHSq77eHQe7FXjJZMBtNFNUKpg7FzFpLEUfHabkqzQaFNbolOnUhiq/c8aIuGcvuVvTaWqC6vFLmPOTBGztenYPmowiaf/YR61VIG5Tw1j4/Jib7L+KCvjqK7BsqyOq7TQyZ2tM86YiS0oYGAO9vJzGiyXg6oReYUFjnRFB6MU0UlNDwUtf0T5/BX6xQywyU1EBFy9StC2N1OQniQ68bjubWlqp/mw/jg8sH5BTjbK10IjAHKa5A/BcMxX1hTPUl/a8BFQ1OZkAVy2Zn6cPypgUCvjgA7hUaIHY0Ahvv02v6okBu0kxOI4LZULFFo6ctcI2KRQboQU++4xNv8+UDicIlHmNJStbRpPahYsZAs2Xyq65ku9ElCqBcX+8i2YbTwoL4fThdvZ/pb0WIamrg507pcjVxQPVFFzUUlvb52KJLnFwoMeeL8HRAb9nlzLuo+dIenYC7j95ANvJsQM/qJHMmTNUbDxCXaOcWrtA1BZCl0mRonhddVbbZGTzRiM5ze4EibkEe7XfZIh0dEjOp7lz4bnEo4x5fgbeLz6HbHzywGUrpqRQUyP9b8xj45k1T9Fzz4heT+Obn3NOkcj4B8IGZjy9obQUjhyhrs2S8rMV5ORcb0he9N5+Gm28iVjWSYO8QaQmq4b8b7KG9JwjFbNn5A5AE+yJy12TMLV1AD0UF1Iq8bp3BoV/3kfDgxHYOw/spaBUQkQEfPwxJKqjmVm3EavXXpNCMMG9iDEvXEhU+qt8sekY2qcTcfQtQZtvoMPe7drqw3dpPDsO11Kcn428tpLi43LsrfKJf9anr7l5I5baWrBtr8LCyZbEv67h4M93USc44//p2+R2TCDkkak4OioIDYXPPgOxXklc2pv4eBpxnO0Bnh4QENC5uNMQoXC2x23+GNyGbQTDRE0NbSW1fGm7Hv1SP5Inq4iLu32FhtEoeTkCAqD8Qg21u87gaatluk8+To+vQwi8WSlVpZJ0uzCZIHZO79SSe0JHB6aLGeT4zgRqCR9vf9Ofu8rBNRig5dOdpGcpcVk7u8eq8APKFbXHVqUddY7BTIqR8lNNZRVUfHMWjx882WmUcbAQRbj40n6sXSwJWDB8iekjBbNn5A4h+pnpOAX37g63mRyHi4eCSxtSBmVMiYmSoE5aayhn05U0VbZJ7Vhv1NToDrUau4dXktBykONnLbB7fDX+d8XjdvBTSvOlclJBY0ng9xaQEvMQWpktp7SRtHxzhGNvZfZcg6WvlJdzVZIxNVWqYBhMjEZ49S0lx+59hct/2oh3jAN+s4Jx/clDFO/N5tijbyMaTQQEwGOPgY2PPelJD1JSqeD855eo2XQQU/sIVGDqD83N0u8w0nF2Jt1rHlMfCeHpH6gYO/b2hkh7O3z0EZw9C9s2G3A7vJGlLieYHt+A88+fuMUQgRsMAZls4A0RgOpq2lc/yIyfjrvlT+fePcvZv+7pfL/0dKr3p3NuQzopASuZNFWa8TNe3k/Wp+cGfpy3o7QUfHzISLwP72ALqfhLFCl7ewel3snEzBia1gxXyT1SjuzyJSKfnDqk5x2pmI2R7zIyGe73zqbtxDlE08CXNSgUUpM4lbWKatcoKcmgrk56Aut0Pa8K8fLCd/1UTJu2oHBzIuiJ2UQnWnDpb1/S2CCNOzRCjmOQA4WT1hGnO0ND+DicD29BqKzo5uD9xNUVtmyB997DrjqH/74ikps7uKdb9bgDZ8PWUJteTv22w8SmvUeYbxtTP3gMn8fmX2u17ugIjz4K8dPsmPTGQ2h8nUmt9OLE85+S9YdNtJaMYhEXgwEyMqj9z0e0/uH/MKWmUbH5GFWnC4d7ZF0ydqzUlK2rnIKGBimqmZcn/TuibC/B1hWS8KlcPnwJCd7eaPxdb/E2pn1+mYaPt+M5JejWfQwG+PprdJ99wUX/xdSL9pw7Bw3HM6ncegLrUM+hGXtHhyTBf++9yCzV3H23ZLOJFzMoTKnB775pQ+oVMRoh9839uC5KwtLtzspt6yvmMM13HI9pobhPCkKQDc4DLiFB6jtVcGkBb6cLPM7raA4fhqlT4cMPYfp0qTdHN9gtnITrnlzy3j+Mc3QbXg/PI+TnH3Pk7ydZ8Nvx1NTAzJlgf3cAW1vmkNRykEKneIRffEzMvx9DsLHu9hx9Qi6XkmXfeYeA3Hxi0935omIp0XM9mTXrW6F6rVZKAOhn9Yu7O6x41pMvO1YSm/EJaedleL13jIBnHPCdfLNWtVotVXAKgg02f3iQwIZmsostKd1wgIqH/svYD57Dyn2E6EH3AuOHH1N0qIjiYqnXYFl2IW2WjoTc7YDr2OEeXd8xmaCgQLo9HBzAsfYyFjsvIMROkMQu3EZWcCv1qzKa3/yc8B8vxW1CJw32Ll+Gtjaa6sBZcYkJD4UT799AylNfIL97Gd5jXG7dZzAwGCRhN5WK+fOl3Paacj2GD3aRFzCLteOGtgt02lcl2NUXEPLQsiE970jGbIx8xxFkAoJq8C4DhQKCgiAwUE27CBtSV3Df3rdRBwZKZblvvw3TpmGaPBWZogtHnUxG5K/vQaFRwYG98N57hC2LoemNPaRsckcR7E9bm5SOsvIvYznwo0p8DYWUmDzgF58S87cHEJSD9Dn9/GDMGGRnz+LrruO02o7z56UeFhERN2yn0cCGDdKyaMwYaYnch74dIBkki38YhsWFhTS4hJD1xmGqHvwvbvdMI+jeCQiK68u8awtpa2vk1tZEeEPEhLuoK5w1Kg0RgLf191Hvq8fWrpggdQljpljjtnTcqBd2lckkm+MaoiW88HznJdPDzNn9DTS/soGYJ6fhOvs2qmTnziHKFaR5z2fMo4lEh+oo/OUnFDonsfihyKEbrNV1cTUvL6C6mtT/XIQ8a/yeiR9SvRutFso/2kfCqnHIbDoRffuOMspvXTOjBUGQGpQ6RXvwdesMdB9vkiZjgAMHyPn52zQXN3R5DLWDBrlaAePGgU6HMu0M0SE62l59l5ayJvbskcLCdvYCU/60kMpGC1xdRCpKjaT/6cvB7Uw7Zw6MGYNngjsz899C3lh3zStSUQHvvw9bvhA45rKMqvRKWj/YhPi3v8PRo30el4cHOMwdS8AYe+a9tASH5+6j6MtznH1xd4/2d/QbfYbIVV278HCYNEdD7KowbJfPwnnR6DdEOsXbe0QZIgYDVBVIVXv1r31G3JpIXO+a2PnGra1QX0/jPY8x7ntJREdD64YvOJ9vS9wLs7pWPh1MDAb48EMszx4l3WcBF9KFaxVLQ8GJTwrwlpXhufI239sNdDR1UJczisOpveBOvH3NjFAEQWpXrU+awNFMR/T7DkNICAgCcicH3vzcjurqHhzI3l7KPwFs4wNxmhFH3aufYewwsHGjlPzn6CIn8S/30HSpApcpYVSfyidn0yAmy2k0sGgRto+sIm5VKGtb32LXO6U0NEhejLlzITcXdh2z5pP25VRXg9DRzkA9kWUyiJzvy5SPniTs8TtXlv1qh9EpU6QI37RpkhBbHx1MZnrJ6RNGsn6/EYC4Wc443zv/9jksOh088gh2gU74ehrQHzhK5t4yxLtXEBw6jFNPaSn6mkaMbXpC609y33oTmh4WIfYLg4Gq3GZav9qH/9oJPVK/vfD6cTJf3DYEgxt+Ro0xUldXx/r167G1tcXe3p5HHnmElpau29lPnz4dQRBuej355BCr/pm5CZkMVqwUqJiwnLRNOegtrGHdOjxbslHlZPD221BU1IMDTZgA8+dDbS0REx2wtDChSj1BUxPs2yc5G1z8rYj56/1EPTKB2L8/gN/CQW5RqVCAIKC5ez4eqyYzq+Q9dvznMgaDZJA8/LCUB9DuHcxR03gO2y6i9ev9sHUrA7U0U1rIsXK+w+qZzQw7VVl11BS3kbXpIrLyUgCUEcFdJ9Pa24NKhZCVSeVbX3Lu3wc56rAYp8wjg9dssycUFqLVQqNfLBNfvAtb+6GZBsXKKgp+/Q5hjtXYz+++e15tkZbmnccIeXzmEIxu+Bk1xsj69eu5ePEiu3fv5quvvuLQoUM8/vjj3e732GOPUV5efu314osvDsFozXSFQgErHrShKG4p6Z9cxOjgjOW65cQXbUOoqebrr6WmsF3i7S2Fa9atQ3biGFHrxxDz2HgEAWbNuv6MdAl3QmWtwjnM6VqX2iFhwgSCX1hKUMpnHHspFZCqWx5+WBrf7D/NpsonkZf0T5C6p46Wf75Jr9oomxkeTKbrhqPJhLb4znahiyKc3VXN+eff4egr53DJPnot/cI20rtnlT2pqbQeO0eB1gXLvV/SUdtyreJrWCgspCE0mQkvLsfRZWhCYPn5UHCiAn1lHQHubZI6XTdcePkQdnH+uCb5drvtncCoMEYyMzPZsWMHb775JuPGjWPy5Mn85z//4ZNPPqHsisbD7dBoNLi7u1972d5hEuGjFVV9JYteCKPCJYbUX2xGDAlFPn4sk0o+xcm6o2eiSIIgJU6sXInnxd0sHVuOszNkZg768HuEIj6asN+tR1Nfisko5YXY2Ej6K66eClaskvHI87YUzXiArRcCSX/udWoPZ3R73MpKyLnQRsN7W9Fv3y194FHaJHDUoNdfS/7RXcii6A/vc/b+/+Pkz764Y5v9tbXBtjeraPr3uwSvjKdF7URSeAvxv1oqbeDYAxn/ujrEvHzKy6H9cjHBY2yZ8c9lg1a91y0mEwQG4vvEAlzdhm4Mhw/DqW0VuLuDOGmyVC7VBQVn6xFSUwh7etYQjXD4GRXVNMePH8fe3p6kpKRr782ePRuZTMbJkydZvvz2/QQ++ugjPvzwQ9zd3VmyZAm//OUv0XQRIOzo6KDjBv2LpqYmAPR6PfqhzHLqhKvnH+5xDAiVlcj37GHij2ZTdLQYg9FA2FNTUG0po2bPVjIS7iIktIcPi4AAmDkDPvuMuMj7OX/enqgopEQ1QRjQBMAufwO9npwNp7CKCcI93g1BJmAZ4UXcL7wwmgwYr8qx39A80NYWFi2FhqkzubDRi+q3jjMpKfCmaphvY2cHJ04oyMqeTOzGD7EyHMfDA/xmBSPctez2Slp3AEN9D9TWQktuJV4736Ymsxp9RS0tZZ9RqghE/sJzjLvHD4NBLxkroggqFbrKOi5/kkrA2gloXEdntURpKez+oJKE7E8I/d5YdGMnsqIoE3nIk+jlcigq7NFvcPmTFNStjqS0OTJjdgNxf78HA+KAhSU7w6AzolDd5v4RRUhOhhvvx0HGZJJ0ESO0lWT7j8NtylSELtQYTSbIfGM/vrOjUPk4dvo9j6a5oKdjFERx5Nv1f/zjH3nvvfe4dOnSTe+7urry29/+lqeeeqrT/V5//XX8/Pzw9PTk/Pnz/OQnPyE5OZnNmzff9ly/+c1v+O1vf3vL+xs2bOjSiDFjxowZM2bM3Exrayvr1q2jsbGxy8jEsHpGfvrTn/KXv/yly20y++FzvzGnJCYmBg8PD2bNmkVubi5BQZ2oBQI/+9nPeOGFF679u6mpCR8fH+bOnTvsIR69Xs/u3buZM2cOyn6UD3R0SDkZ7u4DOLi+cPQoOW8fwtpGwG3FZITJk0AQEEvLSPufDbQvuYcJa3oRLzWZYPNmjh/WIVuzmth4OSc/ySch+xNswzyk8gt//34N+ba/gV5PZY2cr7+REVG6B8Px0wgC6GISmfDL2VhafSsiWlwsaY6YTJKQVXy8pD3SS3XN7Gy4dKKe0LrjnK/ywCv3MG6RjnjdOxOLoCFStxxCBuoe6Iq2Nti1tR3jjt3Y1+fR2iIiqtWI9vZYrl7G7KWa6z9TeTkl/9pITX4LBgsrip0TCV8dR/hY61HTufWqo06rhYOvZ6G4lMF4j0JsF0ySvAjfoke/gSiy+RM9VanFRGRtwfbxNcQv9h707+T8W6dp2XuShJcewcJxZCRynzkD+bkmlt8toFB2/QXo9hxm70flxM1wxPP+2bfdbijug4HianShO4bVGPnhD3/Igw8+2OU2gYGBuLu7U1VVddP7BoOBuro63Hsxo44bJ/VUyMnJua0xolarUXdSbqlUKkfMj97fsSiVkvjp7Nm961k34CQl4bnjOGdOi6SecmdagkoSJ/X3I+iROZz9x2YaJj6BS1AvjMAVKwi4+A4XPt2L7dRFOI8N5eA3Afhn5+J94VOcH1yMLCG+30O/5TeQyfA++hmxlc4caYnHTVuAnawF67x8WgqbsI2TlCYNBjh4EJqbA/FynItX2nYsasqxjErCsg/hlagoCApyxUKxiEiZgkvn48j/6CgVz36ITVIo8b9ZLmmz3GEM1v1oNEopOM4+ShRP3U1entT92N1dqib39pGifnI5cOEC5a9tpTDdgEFhgb27A3f9OhGVU//0W0SjCV2LDrXdIPSX+fa5RPjyS+mzbd1sZFbWfqI961CEBkryyV18x139BkUH8jB9k85E/UU8nl+M57xO1FkHmIJjZTRv2k/kn+7DZgRJrNvZweq1PYgWG43kf3wMP60BX8/xCFfCfl0xkual29HT8Q3rU8rFxQUXl+7lgCdMmEBDQwMpKSkkJiYCsG/fPkwm0zUDoyekpaUB4OHh0afx3kn4eBjYsEHB0qXfUnwcSqytsX1kFbUWOpx2b+G9RgfmP+hOWBg4zU3E9VQptamFuATdRt2xM1Qq3J5fh6ZC6lgXHw/Z02bTsK2QhgwZnpcFwhMG4bPI5TB3LomXXsN4/iiNGluafOPwDhW49KM3qH9sGVH3RKFQSLlrW7fC15VjCWsqx0JUsmj/HqgqhAULeqQ/cCNSTzQFMiAiXk1E/EzKLyVRsffiHWmIDCZyuVSkBZKnQK2GefOknkA3rep1OnIqrNmseRLDdFvcfVXIA0Bm17/z15+6TMbPPkCv1TH1yB+7ViUeAM6elRo8nj8PK71PE6atQ7BQS/LBfXRjmExQ+9Vx5rtexiHGG8Z13+6hvzRWtpP758/xWTN1xFWfRPZAaLagAISKKipKDCSOlSH4+d7RuV+dMSqeVBEREcyfP5/HHnuMV199Fb1ezzPPPMOaNWvw9JRc0aWlpcyaNYv333+f5ORkcnNz2bBhAwsXLsTJyYnz58/z/PPPM3XqVGJjY4f5Ew0/Yap8Skqa+OKLRJqaJBGp4XArCyHBhN4F54qqicv4GG+HxwErEARif7G0T4NSOdngdGV1Kggw+z4PPs9djszKEs/tn2AKEQfEO3ILTk6o7lqIX/EXVFc3UW7pguXSMbgm+pD3f19wIqOYpJ/NQamWs2IFuLgIHBQXYW+l5+WOKcw5vY2gzP9iufYuCAzs11A8wmzxCJswMJ/rO4qVldTYrjNaDSpqbAJY+6xU0KXo65O0tRXxYgaitw+Xf/8p9V8eptXSDacf3NvncfeUykrYvl36f5WxDfuMYwizJ0oqcv3IjxNqqom3uizduu7ug9NB+AptbZCZIVL3+pc4BjkS+vDkQTvXYHL5MuRvKmesvQzDshU9s2DuMEaFMQJSVcwzzzzDrFmzkMlkrFixgn//+9/X/q7X67l06RKtrZJUsUqlYs+ePfzzn/9Eq9Xi4+PDihUr+MUvfjFcH2FE4TXJn5C//xXb5lI8Vi9EFBXDFuOOjgaenUrrB9Wc/emnTPjv/dKKfoAG5OQEU5+KwtMTvvzXGtr/8glRPxRRJo8ZkOPfRFwcnvNzsW+X45O6nW/+qSXmyUnEv/wY53/5GceeeI/4P6zC1suGadPA2VmBu7uCpiY4eWIdJw6mMO7nn+A6bwyu62YjqEa2C/a7ikYD47vXreoSY0sbuj/9H41HzlNZo6CmSYl20YNM+91s7FwHVyu9owM2bpRSqGJjIdyuAZXjY9clbvuBcPIEODvB0qVS36ZBJD0dzr6ZSnhFIZFvPTl8HY37SVERWDVXkBmxgqDoQRZnHKGMGmPE0dGRDRs23Pbv/v7+3FgY5OPjw8GDB4diaKMSS1slIYtC8DqVSu3fKwn++2qwG544q0IB8WMEdKHLOPHEO6T89ivG/n5gtQiuLjRW/SSQr19ai+6PHxP1QxGrKQMcsxEE5EsWYSMI2Mwcy6JXP+fIi8XonryL8a8/QurvviL1idcY98EzWDpYSCXISAZTQIBA/fwk0vYGULxhC7Kzuxn3m4U901wxM6porOqg6IV/oz64n9YmA2WBk/H75MdETbIfkvO3tMADD4D1tWbWAxS6bm+XkiSeeqof7qIeYjSSeaCGoMs7yEpei1ejNUHOg3vKwUCvl0p/feKSWPU91xt7+n2nGBWiZ2YGB5+5kQQGgq6kivw9uYPbSK4HqKyUxP95Da0Xckl/8/ignMPCAu56PoD6Bes4++cd1O5KGZyTqNXg5YXT/z7BlMkiLX9/jVPbaxj7x+WE/XoNlg6du64dHGDGCkfmPBVETEALG/83lff+r4Yjh8XuVWnNjAoqi3WkPPQfDNt30FHTRKu1C26TgwmPHbocASenGw2RAUStlpKi+mGIlJ0upSK1azFLdDrq3/8S5/2fI46fwLpfBHKbmoQRT1kZeHrCmue+u4YImI2R7zYhISijwwiK1nD8oI4O3SC7OIuKupU8t/W2JfRXa6j9fD8Fuy8PyjDkcpj7uD/y+9Zz4e87Kdk6wAZJWZmUFdjaCpaWOH5vLQmPJSK+/Q7HX0rBPdGr6/0FAeWsaXh5iCwybsNv20s0/fEltn9Qi1Z7+93On4cdO6SkxNJSqU+ZmRFEbi4Nlyp5+bGzlKWUkUoiWxJ+j+rTD4n9v4eQ2/Q9T6O1vJET3/+YqvSq7jceTPoZJqm4WMulX31E/fnirjfMyqJuXxoxfk3MetBncAyrIUImg/vuG9TUmlHBqAnTmBkEVCpYsQLP8WVE/OgjjmwJZNaa7qub+oyLC/znP4hjkxGmTL7t6slzrBctTy6l4G8bsfZ+FOeIno2pvb3nN7QgwIQ1fmTYrefyPzbQYVIStHyAEps9PODYMfjqKykoHxmJw6wEYny9Of+bTZSOc8d7vHf3A1yxAlnxJ1iV5iAaW6nKzCEz3Z7EZHmnz/yYKBPaXcfJereGNAt79NYOzL3HHv8k514nJBYVwaVLoOsQ0XeYMLTp8XQ1MHGsXqpPtrMb1mz/vXslY0t/ZTgWFrBo0eBHBvpMRgbtGzax94A1/rUGCuLvZvFvx/Jwsrp/87coUrothbzXdkNkJNYe/c/5GC6q81u4+LMPcZsTT8SD3VRJnj+PtzeofR3AcXTHMX0Gv9hoVDBSb10zQ4VKhRDgT+CaZI59uJnyyY/i4T1IzaMsLSEujopPDqA4cAGXBxdLUu6dELoiBtFowsqtmyVPU5NUFhAcTEqKgIWFJI/Q0wd85AI/bOzuRe3az5rMGxEETIuXIlRWIeTlQWEh2NtjFx/M+A+fRWndg+REgwF27MDZS0UBcs5bTySx9gSlvzxDybx5zH4i+JbVoCCXMf4H49H8eTv1e/YD0FBjQdkvHsczunfGiI+PlFew98s2XM7uwr0iDUs7KHIC22AXbF94bFjdqnFxsHOnVBIJUtjh0CGpCMnbe4QZJSkpdGz+inOpIvYW7RifeZRJkS44e0FjSTM57x8j9IEJ2Hr3MGdLq8Wg0iBraiDrxW2UXqjD7dFVxCwPHq35m9SVd5D2449wT/Qh+vk5XW/c0gJ5eagnJkqdu0e4zoaZnjGSblkzw4j98hkEHc0h9f8OsOBvs662Thl4xo/H8dBJThyqxcJwgdgfe2Jp3/nkHHZPXPfHs7WVPBCHDhGdMIN/fBFAXp7AkiXdeEmys6V93d3xmehDTg6k75NEWgfis4tKFbsc1uBy4HU0LlbYvLMb9VobnCLdenYApRLmzUPx0UfERujRn91LvaUHzb5hhBzZyIEzPoR/fx7B42/O2BMUcuJ+vpgLLk64nN1Fk0FGxo/f5mJSMlEPJOEZ3DOjRBCkpN/gYA2HD99F+o4xLBS/pjG/irxDTQj7X0QV7It1TAAu4wJxjfMYOE0Mo1GKM3l43HaicXaWEjAvXJCMkshIqK81sXdnDpXWQfj4ywkIkIwTd/eB+U37xKlTkJZGs38sQcmuWDpa0mBqRO6qIPflo+hOpWERHYRJd/teJTdhMFDyt09ocAykff9xKtziGPvqGtx8B7f6ZjBprDNy6kef4elvSfTPl3W/ksjOhuXLIaYX+kNmRjxmY8SMhEJB4I/upvaJN7nwdQhxSwZJOMjODnVSDBptKzWpBbz+ioG5y9VERPTjmHPnwiuvYFf8PrNL/DjVNJtXS31YsaILF6iXF7z8sqRmNX48AUGhbNwoo7wc7r6717pjtyCXw9w1juyqW8mpSj/8ig4T8fM3sXluOhYzJvRsdlSpYN06NB9+SHhHCRey6mhWyim/6ykiao9Q+stXaV4xhzFPfsulLQjEPDER4wV73B1s8apuJX/DcbKfOkx2XBxhD4zHI6ZnZQcqFcyaBfHxfthonkB19iQmOweqTM5Uncyn8Vw+NduOUjwhlrG/XtiHbwopcbqmBvLyIC+P5vQCyuo1hDw7H5lKgShX0K6XI9rYonS6/sMIglSWGuqlRX8yFZvSFERXEw0hY6nMbab2dDNpJc3YxgUw+ddD1/3UZILSYhPe3kBcPBU+yVxMaafkD+8S0XCCdpMKvL2xHhdF5MuP4RDeQwNVFGn6cBv5h4rRiRWIa9Yy76HAUesYMBigvU3kyP9sw9tWS8zvH+qyQeQ1YmNHmOvLzEBg/kXNXEPp7YbvgzPJen0LLROfxNppkFZbs2fjlWxNwQ8+J+DEx+jnPYAoKvvuYnZ2lnponDhBgF0th9T2KHRSYv9tsbKSXLybN0NBAXJ3d6J91nLmsh1vvAGrV0stY/qDTAZznw6mfRucV86kqSUE2XtbCL5wGfsH70LSvu8GtRruvRcX1114Loxm4uXdpO88xRnPmYz5WSIuzrevgJLHSPXMVt4QPSYUbW4Fl98/Tvbz/6XpqeWErYju8WdxcgKQw8SJyEQRd0HAPcYFSMZkkOTL+4xOh7GgmPJ92VSdyqep3oSgkVH7p33otAbaWox0aA3oYxNRJscgXE0RMBrhxAksDh7E4kq2rqBQ4KCvwiHKBsb7YrKyod3Wte9j64LycikCNy62jfp2S0pLRHIOl5O7+RzuVecImODBZdtE5MUF+KduIl5Xh97NC6fFswh4cDpWvk69Op9+/xEufX4eg1FAa++BrWAcyIbUQ0pDeRvHT8rQ7z+Mn7GQmL8/Iim/9gSzIXJHYv5VzdyE98rxlB3I5vxfdzLxz0sH5yQ2NnjagOKeu/E59D6Vr2wi/OV7UFn0w5c+bRo0NODWquPui59wxPJezpyxZGFXi/WYGMnPf/kyyGSERco5cxmam6GurhMJ8BupqbnSFzzi5uRQrVb695UdZTJYtkyyO8aO9eHo/ifZ9ckOwk/+F+/HF+I4PbZ7t7RaDYsWES6TwfzHSJyejtPbe8n6p5rGVXNwjBSRK7q35KyC3In/7XJaymej1PRjOf2t8coUMizs+14KYJCrOalLINs9gZr4VmzLsnDUFhP47BKqSmVcOlaLU8VF3IsyMNQUwXp7dr1dgq0lWFu44jT1XnwDFVBRIVkI48ZJBipSueBA99pubIR9++Bcmkhk3RHK/ltLncwFh6JzGOsasHcOwsVFwL01Dx9TAWUVrZicHam3CEDl7kjkRI9eGyJibh5nd1RSOnY5PjNDSE7UjOoy0PR3T9NxMg9Xqgh/+WFkdrdPvDW266k8W4bnhMEVUDMzvJiNETM3IwhE/OwutFVd1JAOEEuWKxAWrOXMU29x7JffMPXPC5HJ++gesbSEu+9GIZMR9uln+FS8x6tn7sPPz+qasNgtCAIsXizVxFZXE7j3DSYEriOn2Y3KSroOHTk7w+nT8PXX6H0CMUVEoY4Ll9ohv/eelKwQFga+vghyOdOnS7vNXayiaepSUjaEUfWXbXjnNBH+2JTuP9/VsI4gIMTGEPC3CGx3nObSm5s4lh7JlL8s6fFXNdIqLhQKmDRJeomihoaGBCoqEvCw1ZJYvhej5VlqrETKGqGpRUkD9oRc/AJ9h5w2vZy68BB8J8+VxBoGEYMBDh+Go0dBaNUSm7UFl8YcoqKgyjqQ0tjJtFs7EXpsI8qWNpxdBLStIh5PLcM6PgS7AEcU6r65MnReAYT8LJDk0V04AkB9lZ72/Sew17ViCA6koVXFbZ2QJhMXfr2Rhop2PMY92GchRJ1Wj8pqlMazviOYjREzt2DjbYeN9wBWl9wGhQKwtiT2xXtJffpNTv/LnnEvTOr7Aa+UmgprVmO1eTPrz73DR5/dj/tztlfCDJ1gZyf14gDkhw4x5+jbjJm2kjcOhBAcLFVm3JaFC6GiAkVBDhe251E/XUn4ymjcpkyBTZvgxAnJS7Jy5U29ZmxtYcaTYdQvfhpBNPXtsyoUOC2ewNip8TQWNfbtGCMQQZCE3yTVWSvwWop89mzc8vNxy8ujplzLUSDg788MebdShUJKcJ7gWYjps40Y/JvRocLSyYLwu8cSHhoq6ZNPmSddV/b22FlYDIhEudpCQH2H6FCcf+8s1rJW/MfZ4fZgMkLwbYxjUST/X9uoulTP2Fce6rMhUpffyLnn3iLmT+twju55l3czQ4vZGDEz7Fh62BP5h/Wc/+G7XPS0JWpNP7Pk5XJYsQJ35TYW7nyHL959gPufs799ot/VyWLaNGROTrhu/YxFzrPZvHkcTz7ZhZyGQgH33IPw2muEjFFxYNcR3itwwyUyhuneVfgXH0YwGKSYT0DALZOSg3f//exKW0uco/uZbTvS0WggKgqiorDT6eCbb4ZtKAIiFm528MOnpPDZt5M24npQAfYdpqXRiE/pCfx+MAn5zGm3v7lEkdpPdpOzp4DA3z+Cg2ffrvGWOh1pP/kYh6RgnKP6mQRmZlAxK7CaGRE4RHoQ/NNVVL+1jcID+f0/4JVkjdAFwUSfeps9n3at/HqN6Gi4/35iGw8RnredXTu68VzY28OKFVj+4AmC5gaRmPoG+mOnaR03AyEqUvKKHD4M778PDQ39/VRmhltIQxCk31yjudUQMdMt1vp6Av93DfL5c7oUzevYd5SMT85h9eR9BI/pW1ixo13kxE+2YOuiJv7ni4b/2jHTJWZjxMyIwWtaMJ6PLqRi1/mBOaAgIF+ykOi1MVh8/A7peyt7tp+PD7LHHmWyVz6mDzdwOb2j6+2Dg0GjIeTpOTQtWkti62FOPv8JnzfN42h1KIejnyKjwhHjS69IeSbD3APIjJlhw9lZygzvAtPpFDJeP0LNvHuZsLh3ib5XMRrh4G8PYNdazpg/r+5ZybCZYcVsjJgZUYSuHkPy7wewikcQsFo2m5B1Y6l++TMMuh7maDg4oHn2EeJiRQr+8immHuwmCDD7sQAS3niK+CQFTX97nW1/v8yeIxYcd15C8YTVGA8ekbwkfe16p9dLT9qRik4nKeJelUY1Y6YnGAxSsupnmeS/upNzkWtZ8LBHn5wZogj7/5OOXeYJYv+8rl89f8wMHeacETMjjr4mqnVKfT3Y2uK9fhouC5JQqHphf1tY4Puz9TiXNfRYwdPGBsCShD+twmNqGk6/+ZyLVWOwfGw2W84H0d7yNOPLdhF0/L/YLJ+N/Zyxvfu8ogiffw6VlYj2DhQ22qP2cMR5YTJKq2HqFVNWBnv3YiqvpKWihaYmKHWJZ8wzVqjcHMy6EGa6Jy2NpqIGql87SWbUSu561K/PjeOOfFqK5e6tRP2/Vah9BkdjxszAY35KmLmzEQR45RWIjkadmNj73eUyrHwc+3Rej4VjmBvrh/WPt+DlXU34/Z7U1KjJyVlCyrEoNG/tZ86UWASNhaR1kp0tSaC7u0uu7M4mcZUK7rkHvvkG4fRp3NrgwPFA0s6NwdlPhY8PJCVdk9kYEtodPTlsczeV+0/iXngShbEDfU0Jmc+/jlJmRLR3AGdnBBdnHCeG4z7W3BnMzA0YjXDkCNUpDVQ5x1HvEEhurlSp3VPPiCiCUFfLmXNK9B98QsL3ZmCdEDq44zYzoJiNETN3Nvb2MHEi2k++xPLgYWSR4TB1qjThDwEab0dmffTwNe+Hi4v0YkIgJmPAdV2VkBBJsGvbNunfCoWkltZZ/w2ZTCordnDA8tAhJvkKWG/7B8W5cRRETWD8+CG0RJB6AM1eZkXFuJlcOD2Rsm9OI/r6YTfTh5aaRkxVNVBTg1hag7K8BXNxpZmbOH8eU10D5ZUy1MHWPHi/Ce+g3h3i0EGRwF2fUXMRkpYHYb9gwuCM1cygYTZGzNz5JCSgP5bB+a9ycawsw2m8LUM5Xd8uDHOLwNvUqVKFxu7dUgw9I0MymlxcOjmoABMngpsbtkFBhE2tpPpvx4nLeJUDjwfiumwCSSv9UamHpoJAECSnjsdSC4yLplBYeLWa2R6wB4KHZBxmRhkmExw+TLkmCO0DC1i0yrmrIptOaWuDi1/lI56pJDYUnH0CpeOaq51GFWZjxMydjyBgf/9SXCo2cyFDjuqpd6mft4Z5ax07neeHkxK/SVQ4y0EQUObWYLPzNcTIKAIfno7g2In8ZpC0hHSNcWPiX+7C3WoWbttPkf/ZpxzY7EDAwzMIWTS07mq5/CaNNzNmbk9pKcyZg41nOPPs+mY4nz4NrvknAahyDMc5Ppms/xwk7NEpqK3NqqujBXM1jZkRy4BWwNrZEfSze2hedi/19gEE7nsDy4oB0DMZYLy8QD1tPPsaE9miW8RnLt+juhpa/vIy4ldfS41zboO7O2Bjg/PqWSRteIGgFfHIjPqhG7yZXiN26Mj99AxF+3KG9rwmEV1j25Ces1N8fCAiAts+GiJ6PaTtr8dHVkLUr1YQ+oOFXPrXDmpO5ZlL6EcZZmPEzIhFp4OzZwfueIK1FctXyFAtW0D75Dmc/Z8NlG0dWbofgiCliTz9nIKICBDtHShKXM5b8sf5+tMWsp7+N6Xv7sbQ1Nr1cdQqgtaNI2jp7RrzmBlOxOoayt/+htNr/k7e5ynoOobuGjTWNpD2ow85+b9bh+ycg0VWFkwf00jy20/RblJxccb3KEmpIObP61HbDFN1mZk+YQ7TmBmxqNWwfz9YWUHoAEUabGzgrrtAqUzgfJgzmS9/SmN2JeHPLxhRwkjW1lLRTFYWhIeD8W5XCgtXU3C0FP3OfdR3nCX6iX708TEztKSmonXwxqqjjrqdpyk4WEChJhKve+9l+hJvlKohyO0RRdoPnSLjP3updIlmwq/ndr25STKQBrTUfoCJigJZjD/Vp/Kp/uGfaNB44ffbR3DxvcNbJNyBmI0RMyMDkwlqam5RZ3R0lGQ17r9f8uh2iShK7hS1usvNribIxS3xpSz4cTJ/9THNz75P3B/uQe04gH3ZRVHqCKxWS4PvZc93QbjeOVihgKBAkaAgL8T77sNkHDneHDNdYDLBzp0UbzxJfYcGo6Ag3SIJn4eXs2C2dZ+0NIxG6dWrRM+aGpo/2kbqwWaapq1h3lOBXe6vq9eS+rsvsR0TTOT9SWhbRC68ehSfyX64Jo6ceiiZDJoySih57i80y+2R/eTHRI63He5hmekDZmPEzMhAJpNiMrW1UlXJlXa5Tk6SmOeGDfDww50XloD0zE9LEwgoPY29rgphbJJkAHQjVOAZYYf9Gw9z5hdfcPLRN4j43VpcojtpqHXVsOiNQSEIUibnu+9Sc6mWKoMjdtE+OC2ZiIVfH5p26fWwfTtCaSlyGxup/a+tLSQnS64UMyOLtjbYuJHiA7nk5kK7WknHuoeIlRdjZSzEwqJ3ITSTCS5cgIMHYencdty8FFjadPEIr61Fp7GnY/8xdHsOsac+EZfHZ7J4nqrL26LuVA6Zf/oCvbsPoTMjObKjhfq3t+BpUYfl/JGVmdxWUEn+Uy/SoRMoXf8TVq/om3y8meHHbIyYGTlMmwYvvQRvvilN4tOm4ezsh0rVvYiXTCY5VV7+cgKTst7Cb+vbOEW4YjszCSE+rktvicZexeR/reLcfw6h1+o630gQwN8f3npLqmDZvBm9fwiEhaG078JAsbGB++/H6e13qDtdR/o2PemFE7ALgxkzrhXD9AyVCv3CZaT98wDqvQeRy8Ho6EJ1ZTQJ861x6KTY5hZEUTL66uqk/7/6iogAX99eDGYUYTRiEgWaWmTY29/8p76EIsrKpOtRpbri0KswUHUyn8YTGTjG+RCxLgH0eoxHT/DlCXeqxWDaHVqxqi3C6d//pjHIEYsVk3t8PlGUqrz374eGina8Sk6Sv/048ueX4jMvsvOdMjPh0CGy06GlwcAp9/uZ/rwPsbFdnMhgoOjtPeRtSkW1ZD5WyWPY/Eo+0Zc3M266H66PPAEWFuj1IyApWhQx5BSQ/tgrKLStpM39Bese8zBX845izMaImZGDhQXMng1ffAF5eRATQ2CALwEBAm+80b1sgLc3LFwiZ0/LcsSU12hpqSLMrwh1kqS8eu6cpOrYmXdFJhcY84NpXZ/Azk7qwnv2LFy6hLy6hs8yI3HxgbFjJSfF7fYTHnyAYNM7VFSHM+bUm9SUx2IYMxPonUdDqRJI+OEMTr3jStvHX1CDK57vv05rnjfWi5NRxoTTpXa9IEB0NNqv9mM4egJ9h0iHXkZVtBViqCUJc5173920rU2S3W9v739N71XjqKf6+10dp7UVfcp5indmsNN6BWP867Ez1dFaXEdHeR2GqjpMNXUkvvccNp7dd4Ztqjdy9pXjnOgYQ9IYI2mfZROiPYtjXgoqXTMyo0BV4SQi7o5Eu2Er75bPo7X4AhEdZ7AWWrCdFY33kjm4xHv1yvgpLITygg5i6k9idek49QoXrB5ajc9c/853KC+HzZtpqNaTXRJEesxaEscpiLyN3QJgKq/k5E82UduoRHH/E6TXOuD5/n6WyI7j+pP5CIkJI6frrcmEeDaNwqdepKXSgowlP2HRk/63v//MjArMxoiZm+jokFZ8w/bciYuDlBQp7HDwIG73+YKTE1FRcOwYLF7c9e4JCVBW5kJ5+2xayi5he/Ayvk77kM2ZhaenjNdegylTYPLkPmoieXhIxohGg8xoYGH9R7yRtZSjR12Ijobx4yWD5xYcHJA9+AATbR357NVxxNfsoeLn/6Z43BSSnhmPvUvP9RDkcpjwaBQFkQ6cP+iA3HsR5WdScfjfnbi57sBpXhLuixKR2dzGY6NSYZg1jxP1URg2b8MoU2KoLiDo0AGKd9tgFR+CXVII8iB/UN5mXKWlkjhbRYVkhACMGQMajRRbu91+ndHUBLm50qupCR58sOf7fpuODjh6FP3GLyhptqM6Xwsd7SQbjiFXKehQyNG3C8hmTMf7/pnY+Dli5dp16E2ngzNbS2l/8wM8Ck+SaB2G8sNyJsqMyDVq2sLikE1PwndmGG4OOip/9xqXT9UTabxEvX0AmoXTmfpkODJ1J9+JKFKZUoLGww4brxtm044OaGkBGxv8S07hn34UPJ1h3UoIDEREgM7u0aYm2LABY7ues2VuNNt4EuitIyhIcYt9J5aVI1hb0XomgzMv7mV3/Vjs756JIlfLUv27+IW1IbvnUXDrQ0hxsKioQLycQ/kvX6G+XqA5LAmdxp7ycslxaWb0IojiCKprHIE0NTVhZ2dHY2MjtsNseuv1erZv387ChQtR9uZh3wuamuCrr2DWrGF8BjU2Sm6GPXsgLQ3uvZcquQevvw7f//7VZnS3x2CAy9kitqYGdmxuJfnoPwicH4rVstl8dCyAI0cFgoNh9eprqSk95tpvEBmJ0t8f9u8n77PTHDROodh3EitXy4mI6NqYa2uTDL6OSwVkv7ST6oJWHO+ZTfy90cgVvbMCW1qgtVXy9pSVmMj9JpuWfaewbSjCamwk3ivH4xLXmXUkUVVu5ORnhaTUBzIuQU9bRj7GzGzsqi7joG5FHhyAw7RYApZEd/5BTp6UXm1t4OZGc0kDhlYdDn520qCcndHbO1PQ4oLRyxetFrQtItpWgbiwdjwv7ZdUq660RTaZoLZOwMVdDgoFOqOcxhY5Dc3SK+yP69l/5tCt90BdnTSOs2ehtJSOuhYMja3o2k20tZpIcZ5HPgHY+djhH2dHzEIfHH174JXS66n6ZA/CZ5+iKCmkqUEkVwgiJ2AO+rAYPCYHsXytBQIipKSg3bSDqjIDCgUY/YPQLl2LpY0Cf3/J2SOK0rVh0rZR9NV5yr9Kob2yEZ/nlhO8OPz69/rhh9KFXlQEDg7XY3pdXVgmk5RQYmPDwbIQWuR2JCffJs+qrY2cH7+Gk6uco4eM7LBczkTLsxjdPFlhvwdNUhQsWNBpluxQPIc6QxSh+O+fojh1jJb0Qko8kykMnkXMw2NJHCsbMY6boWC4foO+0NM51OwZMXMTtrZSBcurr0oN16ZP73URSP+xs5P+O2eOtNJ+911c164lKMif48dhbtcViSgUEBEpAA7cF+rA6X8tp/it/8N941YWBQXS3LKEHRcSUCicuf9+epZr8W38/aXV/9y5+IZFEfg/W4ksvMixjctwfdqzyxwXyytVh5pIf+JffpzynefJe30XB3edJPh78/Cd1PNGctbW13NXvXxkeD0ejunRcApOV1Px5WnKTxZ2aYy4eshZ8v1AxpSAjY0Su6WhiGIodbUilenVNKdk01J1G00TS0uYPh1x/ASKt5zhVKUf6QovYuNb0Gir0WXWYKysQV6RimVTJfqxE+nILaFV40xe+EJkMgvqfBbgFTYOq9MHyD7VSPo5I2UTVhDiZaSi1EhTvREHWyMePgbcXYwIlp3k/lwJyeDiAvHxtNh4kHmwCrcfr+RUbRCZGSI+7nqmjVMRGdk7pw35+bhWZUC0B+3BHsg7TCQ6ORP12HLkGjVy+RUDo6UZLC2xenQtAZaW0ndjaQlqOeg6ECvrOZTtRphlEY37Uqg9nEGTlQcu8ycSd3ckGvsrk35LC7z/PlRVSdbLypV0a91eRSaDGTMQRRgf00WalChS8q9NlKQ3kNsB572WMi20jtj8NDQle0k/r8ZrSRJevdVlH2RKzlRQsD0Tt4pCbCO8KU1Yz+LH/UacirKZvmE2RszcwqRJcOYM5OzKIy/LmzX3q4bvhp80STJIPvqIGZNW8PaxcKZMuT6hd4dKBZN+NJFyZQklH3yN1/4DLHAsIFCTwMX3Q3i5eiVx4yyYP7+Xk9QNKPy8iPr3EzhlHsHpvXfY+9Nkkv9nOgGhPTigIOAxPw7XaRFkvnWM/H9swTPxaRQWfb81ZTIIHOdC4LiFPd7nRg+RIICTs4DTdFeY3nUL9upq2L5dTX7+Fc0TAeoNNjhH2+AxKRBHYzWO57VYFlUgGA9R6wU5+QWEHT2Gw2ktdYVNnC3XUteh4ZzlBESlCr28ECfBBj9fJV7jlTi6WWLnaYXGybLz5ElBkD6AtzdZWbDlHHREiVgf1xObBE8+JeDi0seJNTQUfvhDACyuvADsvr2dra0kevFtamowffwpqfkOtGTVkW7Q0hEeh9+PHid5quvNocLGRskQaWqSpHjd3PoUMxWErqvbtdsPUrAnhyYbL0p9oli51pbQUx+ibcmiIrsJ9bL1eCTe3oAdLgrfP4hOUHEq6Xs4rZ7N2nlCp42tzYxOzD+lmVuwsZESMrP3KEg4+h+sp8wF5+jhSyQZMwYsLXHftIlow0JOnRrDtG5yTW9CEPB4chlOunIK9tljl3aAhBgrsmr9uZxpYMKMvhsiV3F2k4PbNIIjI1D+ZxtZL/yX1qeWErXIv0f7yy1VRD8zHdMTU5ApR09JgIsLPPCAlDZSVSW99Hopd0a6XFwgYRVotXScPk/V56noksIob1Gjar2AM1n4eIlU1cjQNFwAbRsyoR6bbDmqy3qa2vTUtRuwmT+J+B9Mv+04TCap2uTwYenfgkzAJ0jFzJkM34SVlYX+sy1cTO2gqamewtAldARF8uBjyluqegDJK7JuneSq628C720Q6+o5eFxF/vTvEznJgTWROhxe/wu1KQWkGsbi/OrDjJnRF1fh4FKVUUNOkyv6u5ez8C4VXl7DPSIzA43ZGDHTKZMmQUCAL/X/dCbj/20idvFplMsWXmmAMgyEh8O6dUx6+RO++aQV3YRJvRN9srBAtX4VIWtMlLwWgfDBe0x32IdfaTkH3rwHQQhmxowBsLdcXfH77cMotpwi/+MdGOY8jkLV84llNBkiN2JhIVUGd1od3N4OFRWoBR1BCXbktwZwTgjinM0UnMKMzAnOJ9x4mYi5c8jIVhASIjnDekNzs5RSERsr7WtpOWjzefeIIpw8iel0Cnmt7ijirPBzsiI40RGbSOXtc56GYIat1DkQcv8E5gcLyNpbMW3eQnaOjKOBP2DGD+LwDxiZiRen85wIf2oGycnD+LuaGVTMxoiZTrG2ljzUhhemkfE/+aRvLyLaPwOli8vwteYOCMDxhQeJ/OVm6kvicQvsZTKLlxcC4POHp2iePRb9L/7B+AkKNKc/Iee/42htnsnCJfL+P+xkMrxWjMfzrmQE+Xf4yWkySfG+/fulpExALQgsdG0hVnmUM5lWuPpruFSk4UirM64Zl/CP1KCK9KfzUpHbY2d3PdVo2BEEGD8e2fjxhA33WL6Fu0MH7jmnKcx3xvnEV6RVeZIe/SyrHrHF0XG4R9c5ogjTpgtmXb87HLMxYqZLFMH+RC7y59gJOSmfXCZp8iQUVsO3ehc8PUh446neLY9EEQ4dkgLpUVFgY4PNjCRsvnoJPv+cOHkTxpRz6N8pZFvdChbf5zAgrv3vtCEC0m+UnCyF2TIzpUqX8nKE6dPwaWvDaWwr+sZW7JT1tFSXUpHbSt3mdmSLvzcsw21vNVFbJ+Dlfd0QatWK1GTX0ZhRSntBBUk/mzOie7V0ickEmzZhyM6j6IySPUELUI2L4YF7hD7J0g8VgmAWGP4uYDZGzHSLYuVyxq215tgzG0j50cck/WM9cothLCfrretCEKQkmNdeg507wc8PoqOl18MP47p7N1ENKVwo0+Gw6TW2Vyxh/g+jehcGMiMhilLMpKpKCulZW0sJObGx0quuTirPUqvRgDRBtrdjrdEQPExDbmsVOb/pMuXfpCEsXkSOtpT23FIMhaWoqkvRKHXIPd1R+nthaNOjtBqlF8bevZCdTe4lqJe5U2EdTJKbMHTXuSiS81kK3vNjsLDrun+Ume8eZmPETPfY2aEGxv9jNSe+9wFnfraRsS/eMyryG4xGSXnVykqD65x7sNv8NrKCAmmCHDNGCjktWICPnx+tf91GcbM97qe2sv+FPKb8YT4au5Fdwz8i0Ong6FEoKECsrKKtro26dg2XwpcxebE9alc7ri297e0lhdCCAigowJhfSHHySjKbvRk7SSUlAg9RonRrK6R+WUrD57uxrinATpCh+SADG38n1IFeWE8KxS5yhtRHaLSXbaSlQWoqFW6x7KkKw2JKMEsmq4mMHKIcDJ2O7Be/oPhEKTZRfljYmetxzdzMKL/DzAwllnYqxv5jHae/9y4pv9pK0h+Wj3iXtVwu9cv74ANoavLCu2IB4S1nSBDK0GzeLEm6WlpCZCQhf3VH+7tteKxeA+/v59J7Jxjz3JTh/ggjH5WKjrGTSc20p+XUCZR1bXQoZRhz95D6ZS2KDi1tFg60q2zxd25B01xBR1UjWitXGtvUGPdsQCNAyQdQJMgwyZWY5CqMChUmuRL3lVMIWtq7pnLX0Gql7nLjxklGjihK79XWojh0guDtJ2gur0cV5I1BVFA8/T6SHgy6JS1Kr+9/xdWwYTKBszOG539MxhEZy5b0XuyvX9TWkvenT7lcqGHMPx7HLWSohYvMjAbMxoiZXmHtYknC/93L2WffJvWPO0j43/kj3iBxcYFHHpEMkhIxEZ2rN8rJ1iQWf4Hi1Vfh7rvBzw+ZsyMJ/34QALdkv+Ed9ChDba1k/FNjKI13omLbSYQT6VR1qDFpjVx0mU+N2gdbSx3VmmbsrRqxsirHNcYdm5wijrrcRb3JjkVz9ahEHTKDDkGvQzDokRl02Ed0rXXSKbW1cPw4pKXRZNBglVuAvLGO9vJ66qv0VLbaUKJ1wGAzFeeFjsQ8kICds5IgoxGuGCLV1VKqS1YWJCZK6UYm080vhajH2mGEWykyGXh7owBmzhzic1++TMHfN3FGP4bJ/5iDp/d3PI/KzG0xGyNmeo2dtw1xf7+fC7/dTFtdGxrnXtZhDgN2dvDww/DRRwJJSe6cOgUHG9Yz1+4kUe9+iHLKBKlr8JUl8WgIQY00BAG8E1zxlvti8qqi4XI1Go1AUMUpqgoPYi8I6KutqemwoU5mTWu2DhvPEGaEVmA32QUrKxX2XXVA7glGo2SEHDmCUdtOYSEUl7di5ejL5boxlLQ74JTgQHCEksQQKa3l21GhoiL45huoKDUiiCZkopFvcvV8aWGNprUG+8ZC7BqLsGsoxD7MjfH/Xte/Md+BNDeJWJ89TMGHR9hvtZgFv47Fw2O4R2VmJGM2Rsz0CYdAB6a88/CI94rciEYjCXTJZBAfD7m5AocOjeewzp+5X2zCPysP9doVfdSHNwNIuSHjxiFLTsaxsBBOnyZi0iTcFK40l7fg59iM2NRMS0ULdYXNNJU2oCvU4bU6ZmDOL5fD5MkUek/im89baHeoQaOuwV4RQNTdziwL/paGicEAqalS/pBSCVotvh1lPKI5TWvmXkpl3tScLUHu7kLyfEcEmQ4hwhvBzxfBP26I4x2jgJoasLEh67dbkFWUcarYnzFrjWZDxEy3mI0RM31mNBkiV7mxciA4WHoVFrpzeN/jpO3fxZjTr+L1+CKsJsQO3yCHA4NBEidrb8dkaYXMqod6+7dDEKT+Pc7OUFKCY+VlHCdMAJU9AmATBd30O+wzZWVw/oKAR6gNYogNohiAszPExNzgBTGZpMzmAwckDZScHKkDcUUFlJcjb2tHr7emqb4V9azJhC4KQRHnJ3VtHu3JrINFWRls3kxTExSkyakqV+Pm1UzwzM6U8MyYuRnzXWVm0LjaD3qkd9P08wO/h5SUzl1E2qfBFP9mK94rGwh7bOpwD21w0ekoeX8f1d+cwdhhQK+HVpk1tj9+grH9yS1ob5eEzrKypH4rgF5jh1Kvl8p6v/3SaAZUSM/TU3p1iihK49qzR8oruYqLCzrvAFT52Wi9w0hP6aCtvp3AB2LwfWTOgI3tjkWvh82bMVXVcHq3jpYKNar4sUT+di5OoeZpxkz3mK8SM4PKnj2gVokk2OZgHRs4fOqtPcDLC7xeCKNq2VPIMQ73cAYflQrvR+ejjIsk9+Ud6ArKQK6j7Q//x/H33LAM98MhzhfXJF8sXXvhx7CwgHnzEAMCqdqRSs3xbFosLQj3aqejvhZDgxZ9gxZjkxajth2dDtqwxGJqMtHPzhi8zwuSZRweLpVYNTdLr5YW2lR2bD4XRGDoBP5/e3ceH1WVJnz8d2tJVZLKvoeELGRjD2tYZFM0CiK4b6Nou9s907ztaOs70+3ojNPT2t3TY7+29vTHbrS1u9FuFREUFQFBQkBCBLJBQhbIBqnse6XqvH9cjCKLgCQ3lTzfz+d+IDe3qp6qU5X71LnnPGfzZph4g75o9FAuBjZUKAXaxx/TfvgYB7fWohph4j/fy9SHsqR0uzhnkoyIAaNp+ho3L72kUVTSxvT2/yHkqlmMvnYaFv+hW/QocsxAXUAYmqJmjCbyD/dR/nY++3Z1M+e+8RzfU0XL/ioaV2+j/Ll6zGHB2FJHEzgxgcjpowlNCz/j/XV3w+7dJvLy0mlqTseW3EpI02E+rsjUO0IiwT/pRMeIrY8AcycOrYPwUYP0nviypKfDATEx9PXBX/8ElZX6DJrbbtOvMIlv19zooWpbJb6fHaHmCzP2ydOY98xN2GKGaG15MWRJMiIGlJ+fPnP2ldVTOLL3C/zWfYhW9SnMmnnS7BVhLM2kkXz9FEZfozCZNSJTJsDNEwBob+im/vMjNO+r4thHX3D8w73MW33PGe/LbtfHg0ZGQnU1VFcH0tmZyWPfO12tDgsQeGIbfErBunV6IgJ6yZkzLmT35W363CglM65cvR52/GQjR1QcE484GbdyJhG3XT7oY2qO7a4kYtporxzDJr4iyYgYcImJcMk8jZrAqzm24SX8DnUzeqEv2nBNRNxuMJlQaPT26kviDJZjx/RpqTYbhIZ+tSUlndvYHYv11IMc4XYcV6bClakA9HQr1q+HQ4f0AcE+PnrSuXTpV4vVORyQnq5voJ/0vxxDdK4Go9DYzp16T87VV+uDmYN9e8Dlwu12UFoKaakKrakRqqtpK66melc1zsI6YlfdTNIVqQMb3BC361c78Cv4nDGWAzRduYKgW8YO7hlFKer/vp3C/91Oxq/uJ2ZC2CA+uLjYJBkRg2LhQnBOjMA8+hI2bzXR9D9byOh0Y79s7tAf4Xq+lIJ33kFzOqlqiaTgeCRh46KInR5LfIptYNYC6euDHTuIbG3lOpvG5q0mjrVp7I2dwfTsMJKTL95D2ewaS7LdfGFvJuc9J83mQJqiosnP15f7CfvaOaGnB47V9NHS4GL89LPP0Ompa6J++0Ga8qvYFbOcpHQfLr104MqVK6Wv4zd7NnoCmZdH27otHAidT9HOFkaZ67D61+Csc1HWEU1dRwD+jgBCAv3ofOljAhJCCU8fuSdAU852omIgLN5EyPX+mAdzyR6Ph/Y16yl8/SDB/+duSUSGAUlGxKAwm/Vue1bM4+olJt5fnUbr868zvrqZsDuWDNICGYPEYoHly2HtWlKP5mGphf2FcWwuvQtHMNxxh14V9qI/ZlYWbNxIQHEeV4VC/nFflCuSvdvtVFT4M3eu3lNxwbmfUnpNjh070JqayPR4SLXA+6alRMZ7qK0M49OtPkSaGjDXVRPYVo29sQb/jmM4l96J2TeW4DAzwcH6pRxNQ1/XZscOWnccoHx3A01N4Db7EOP7B7re11j/PxqaCcxmDbNFQ7OZ4IYwdjz0GvP/967v1DWvaWA2KSgswv3hJirznDSUNmOq/zW1tqV0hPtS7E4i2NpJakAdM0bXY02IRYsbhSVxMkGxI6usubOgjrDx0fS1dgKQdWsytsxJ+oDgwayV39tL75//xp4NTbhW3suUq4IG77HFgJFkRAwuiwW7BVY8FENu8r3sfuF1Uqv+SvJjN6DZvHQ11NMxmWDFCrDZSDTtobO8GS3vZapTFlBYkM7cS7SLf2ndZoNrroGxY7G++y5TlkUTVbaHGPd7VJTFszs/g21x6Uy7PJRJky7g0r6m6XXR4+P1hfH278c/1MqKkHz6ijdhpxuX1Y/6emgoddJW7qTLY6PP15ekj/6Xjs1m6ty+dGn+ePz88Qn2xxbqjz3YThAxjLk6HEt9NfXHTOyOWERSoiI9TdHn+mrr7vXwhaucqKum9CciLS36bN1x4759vMcp6uvB6cQcHcHokMPY+iqps/kzybeULi2CubePInZ6Mlr8lXo2PVwvLZ6Fu6mVgl+8j3NPBdNX/wB7XxsApltuGvwFe9rb8bz2Zz7P86Hmyu9x8/XfsR6OGDIkGRGG0DSYdWUwlYnfo/DJNbT8cDUT/vM2fEIdRod28WgaXHUVWlgYYzOn4vyfPcxrfY8vfr+Vv3y0gNl3pZOSOgCXqFJT4eGHsTidjF4ZB62tpJaUkFxQTP2ujzn483D+HpJB4pUZTM6Oxu57njFERsK11+oLnezejWXhQixmM3R1YXU6iWtsJM7ppLOshsYt+2jLO0Ttwse59OGx0NFBT2MHbXUddBzroPN4B93ONpobuwlaPJ+Y78WRUFtLQkQEvcp6yiUtl8vFFxvKCZoznk8/1ZOQmhrwUx14tuVDby8NExehel2YOtv7N3PXV5vN38Ksp67S7zA6Gjo66Co4TGFbCu7RMdhVF0EzLsdvxhwi5oE2jHLk8+Lx0LZpF8W//QRnRAbTf/cDAqL9cbkMeEEaG/WeuddeI79+FPkTVvC92yzDqkN1pNOUOt9hZSNLa2srQUFBtLS0EBhozIj/L7lcLjZs2MCSJUuweu0Soqdqa+pj97++g7X+KNNevA+/iKHb/f1d2sDjAZPbhWf3Ho78dTtFVQ7U/AXM+V4GQcGDNG6muxt18BA1m4up/fQQTd2+TH7uDiLHnXmq7nfm8aDcHjTrd//u8+XrP3bsEsoPW6jLrcS34HMinUXEx7rx2Hwx4cHc1wMmEx5ffzx+DpS/vnn8HJjDQ0i9eeqZQqWkyEPG6E60AMeJx4TGqnacuaU0bT+ANTQAV0MrmtXCnN/c+p2f05BUXU3t79/jQF4v5muWMm9lcn8nyKD/HTp0SC+i19xMse8U1nUt5t77tBG9aoM3nQvO9RwqPSPCcAEhFhY+fz2H1hbiGzb0F927UCYTYLJimjOLhBnTiNieR+krG9ixcitRNy1g8s0ZmC0DnJTY7WiTJjJq0kRGfb+PupxywlMH+K+6yYR2kb/CJiVBWmwHRDhpT7PRsD+KKK0e38RQ/VKVw6HP0z3Hx3XXHefwn3fyasV8ZjrfpzvBhPOYG3dhCb61h3F01OPBhDs4Fve8eYTMHU/k1GG0Lk1vr37drrcX90efUPrmXvbY5zL53y9h/GQDTxO9vbB+PQ2lzXiiY1nXPotbRngiMlxJMiKGBJNZI/268UaHMXisVvwWZTHpkqmEv5dH+Z82kFdVzYwnFg9eDBYL0fO8eHqqwwHTpuGYNg3Hregzio4d00cHn2MS4mlspuzlLRxZuwdXZS3LOl7Az9yN2+aPn184roQUbNcvwzF/AtGzkgiMPPeSrMqjvKP2hdsNb7wBaWl0fLCN3LJwjmQ+wDV3hxt/0t+6FdfxZvIPB1LTN4Er7/UhPt7gmMSAkGRECCNZrcRem0XUkmn0tvUYHY13s1jOsijNNygF+/bRuW4z3buOEeosx2xppzpuEh3hASTNjGD8U/dhsZ37gNW2Zje1e2po3ltOV8Fh7LGhZD1zzQU+mUGiFF1vvocrr5SOXVVsYClxt07iHy7XjB+rW18PZWUcSL2Wz8wTUCYz0Y0wQQ2/agBCkhEhhgSzzYKvTT6Og0bTYPJk3ImTCW/30NXQQW9jO1EuC7a4CBLT+uAbJ7yODqithRR1CE9IGMdcIdTm19OSX05X4WF8airxCzBjTU8iZvF4ImePMea5nQfP5q0cXLOXri5o8wlg0T86SL588M701VtLCZs0CnvIaWbF2O147nuALc9r2PwgOxsyMyURGa7kr58QYsQKCoKgIBOMCgC+Pi/4qz+NfX2Qmwu5H7Yw9dgHdNQVUe6TRmDLUYID+ohMSyBwWRLhMy7FnhjtPWfL4mKKtzewM/IaGkPGMGFuEKMHeJ3Cfn19HHppE0fX7iHxiVtJujTp1GOCgigqgJgYvbrveU/bFl5FkhEhhDgNpaCoCD7e6MZ//04mV27Fx9xLeAIkTPYQePUtmOJHeW3tkQpbOm+qDILHwaTgBiKq87BYTj/L6GLyHHdS/B9/o+oIjHv2AUZPOXP11OhovX6Mt+R34sJJMiKGhYYGfRszZvDrMI0kdXVQXq6Xee/t1f8NDIT584ffCcPl0lcWvnJ2C30JYfR2XkNvh4ugNBcOhwaj44Z05WC3G44fU7QU15K+6OSxNH19UHVE46ar2mhZu4XudV9gmj91wAfduvbso/C59VSETOGSFxcTFnX2U1CYVHkfMSQZEcNCWBhs3QpvvaXX/Bo7Vv93MBepGwmioqDuaB97P3Cijjfg19mAKzWSz/3GkpgI4eHDJynx8YGEBCAhFAg1OpxTdHXphXBnzNBnMdfX68libS3UVnugoICEI9sJs3fgyfoBJr+vZgL1tnbjl/MZ9R/vxD4xlckvPURIygCc+ZXSi7e43XS+uZ59fz9EzczrufKf0vAbvrP4xQWQZEQMC5qml5d47flGet7JZfOnY+j5hySmZUk3ycWkHSwh87MPmOBuoqIVqqshdPR4jr7jJK8tBHdQKJHpIcSn2klMPLEeUU8PbSXVHPeJo6HVB39/fUG9oUJ52eyMnh59DMtnn+n/Ly4Gp1NfOTkmoo/UjnxmHPmMwBiF351z0aZkgsnEjh0wdVIfRa/upvndT7GNjmLsz+8iauqogQt2+3YOVtmJKt9JzoEA+m54kOU3B3rrlS0xgCQZEcOG1QorvhfKO1UxTC38M+7/tNJyVTJBc8bDxInedcYZqtLTISUFS2EhKTt2EFNWh2l6MBN7avE4C2mtaKRlYzudr7ZypNVDRVcPrg4X7b4RFM+/D7fNnzETfOls9CM4ykZomEZw8AWsk/MdtbdDSYl+Ir/kkhM9IF6gogI2bIDjx/UkytrbQVqaP7Om9BBQ8jnazhw9K7ltEYwfr49naW6m6KWtfFGRSHf1J/gE2kn58fXELxwzsJ+Jigqa3vqE2nzFrpRFJD48j7nzTPIxFKclyYgYVkJCYMEPMwnfe5yGtZ/xxRslBPqOY9IEDW+oP+UVzGY9uZswAf+KCv0aWWAgJiAYCO7qguJi3J/l0LVzH501bTiba/Br+Ijuxk5G13XhWu+hqdtElduXXrMf5gA/7CG+RF06nowbJw5I2EpB0QE3JW/u44Aaj/vEmvf1ld3YOxuxdzj1rbMRe6eT4PRo5vxs2YDEcqESE+Hhh/XxIJ35B3F9moPLGU/gy7v0a2TLlkFa2ldJRnMzh3+6mvp9zSTayimMnc/YxC6U1WdgE5H2dtxr/sbBYkWfpvdOhkdokoiIM5JkRAw7yclA4mUE9jYQ2GTm4Jvr2ZR3hOlPXE5ItAwi6ed26wMPOjv1zWSC0aPP/faaptdl/yZfX5gyBfOUKTge7MNRXExkdTUZV2Rz+DAEBSrCA3qgsxPV2UXH8U5a6rpoP9aJI2aAFkrs6UHLy2NcTg4JqodxAVU4DzrpPOJkQlIHfmG+eEaFoULDUKHhqJA0rHFRAxPLRWDet5eA9ev08RghCm65Re/e0TSamvSknOZmSp5YzZH9zXhcfXjanKS7NhLmF4Gv3wB2BXk88PbbFDZGk5c4iYhL0pk/zyaVU8VZSTIihieTCa67jvCeHgKv66Pwv95lzz2/JeaBaxi3bIx8Qysrg/Xr9dVQT+idNZ+G3nBC4/ywn3vV87OzWPQBIhMmoKHPdtKridn1dXJCwREH35qCdHZCURGeo9WAPkjzpLzJ44G+Pjw9LrpaXZjsPvo6RycqrfLhh3rVMsDfDOmT7ZA9jd6AMLp8QwmM8ZLRlErB9u2waZP+c2CgPjBn9Gi6ezQ2boTWVkiI7KLz3W3UN6eTkHacRHWYkIlxBC5biJYywJdnurtpXHgd9TH+3DodgoMH7qHE8CHJiBi+bDaw2fAJhMz/XknVW59T+eIatm0dz9QnsnGEX6wzrhcaM4bu7z3MgdWfY9q2la7WXlpyCwjxfIr/vDBMqXH4JMdBXJx+sjNixGFPj17oo6CArgNl1NV4ONLmgJWpND7zIi3dvbh7+ujrduHuceNy6VNWAQKXzmPqo5f1V1plwgRobtZHejqdeiWtxER8AJ/Bf2YXrrlZP7s/8IB+ecxHj76kBN57D3qc7Vj6uvGb6Mfkyf5cWpuLT0IMLFipX+MZjCzcz49QP1gsPSHiPEgyIkYGTWP09TMIn53K/mfeZffdv2X0w1cz5qq0wXn8khJ99KFe8lP/RhscrBeyOAdHjugn2sBAfbsYtVTsDgsT7p3F3nGTqVuzjcKIBfjb3exvPoptw1HCuoqIcH2Mn82DKS4Wa1Ic9pQ44i/PGJwF4KxWiIyktrSDsiaFu7aS9hNdNkcmLiE8yo7dYcE/wIo9wIpvgAXfQCt+gRasPt+Iz2zWT97eXrgiJISvr16nFOzZo3f+RNmaGVP+Kj3+oUzMryJschzcdZv3jM4VI5okI2JE8YsNZuZv7qD0zb0cfXEdUVMfxBF1bgnB+XC79S/2vr4nvoympelTIDZu1M8gADfccM5zXMPC4M039YJjoN/vFVfAlCnfLU67HWZf6ot7wRWkFughXnZZGl1daTQ3Q5PTQ3tFA92lR3GXHsW0Zxejr8j4bg96rkwmiI0l5oZYYm6Yi8fl5lh+Jbk1+0lckMDEiTJtW9Ng+nSYnnAc/vQnSG8FSyvcdtuJwVNCeAdJRsSIo5k0Um+eStLySVjsA/MRMJkgPx8+e7+VxPpcPH4O3AFhjI1YRGLZJ4REWmHdOjh6FGbOhNCzF9XyM/fwD8EfUVRXQcVRCx6ThfbDdg7ev5yUKQHfuRCo2QyTJn31s6+vvsXEmGBCJBAJDHyp8LMxWc2EZcZDzX4yBikf8grV1fD663pPUmoqREQM/lxpIb4jeceKEWugEhHQv7HOng0tLYG88Yt0ssr/ih+dVIeCfU4kfZOmEDIhDsueXHjhBX1kZ1aW/m32dNf1bTbM1yxlQlQuwas/pqOlD6vJn7zf57IlZjzjL4tmylRNqlqORD4+8MMfSrlh4dUkGRFigGgaXHUVTJ06mv/37/eR/vnrtDQ1su8TJ40HjtIyLp7gCTcQn9JKctPnxLz8dxxR/ljmzNQHXfr4nHqHs2YRl5yMa81bWMemkNDYjHPHHyn/rT9v28YTPn8ck7JjiIkd6dOFBt5Ar+NyziIijI5AiO9MkhEhBlhUFPzf50LocN5L/esf47NwDkff2kVv7qtoxyLpmTKLPbELqAucj6PoAOk5Owm3bMJ2yUzSHrz01DuMjMT60L3Q2Yk5MJDIa11ElpaSvqOQus2r2f83f/LTx5G4dDxpC2IwW4bACdOLtLUqtLZWHKOC+vd1tbtpKHHSUlxLR1kdvVV19NXUM/eNVfg4vGo+jhBDkiQjQgwCX1/wjbMT/thS0DRSs66kuW4hB9/Ip+3jTYRYPmRK9kwib5tGY+dkGvOrcLUcO/MdWiz6tBrQxwqMHUvw2LEE3+kisaCMyvcLcf76FT79bQDz//owZuvQXV12qGhrVeSvKaF93WaSstNodgfQXVGH60gdZucxfGwa5tgobIkxBF86gaD0xQN6qW8oUQqqdtfTcaiG1JuG0MJCYtgYGZ8kIYaKr40HCY62M/OfZtH34EwOrT9I/bs7Of63rfjPmcz0H2djvZAqmVYr9swM0jMzUK4+ju+vk0TkW7S1KvL+dpj2dz/Bv7kaX6B5Uyu2pFEEJ0cTeOUcgjOi8YsL5TuPFPYyHg8U72ql6pXN+JXtJzg7y+iQxDAlyYgQBrP4mBh7bQZjr82gNq+W2k+KLso3bs1qIXJq3EWIcHjrbWglweGk67IkehrC6XW2ERxtJ+2J640p9jYE9PbC3p09HFnzGTEVOYyZm0bCkw/jEx2Ky+UyOjwxDEkyIsQQEjM1hpipMUaHMaKEJQcRljzT6DAM1dkJfr6K9ooGckvDOPpuHuk1m5k9OZSYx+7ElCDlVMXAkmRECDFkKAVHqzwEtx0hoOsYzJhhdEjDmlKweTN0dylCd31A/YHjxDpauTrRQ+hDV6ONzRicEvJixJNkRIhhoqUFGhr08awWi/6v1QoBAUP7aoPbDZUl3VRtLqNlVwmO2kNkJHThjIile3sDSuljF5QCt6YgFfb98iM0t4bHA0k3zSAsPdzop3HuenroLCin7MMy0r+/GJ+A09cH8XT30njISfjEgekpc7th7VrY94Ui5fCHJLtymZgM/tmXwKJFQ/tNI4YdSUaEGA56egjYsYWanEb2FbjB7UaZzLivXs4NdwcYHd0ZeTzwxRdQuFejrVgjpMeEPxoNDdDtgU6PCZNJ/3JuMgEWvZR+T58ZCxqaiaH5zb219avZTkrpywyXltL+RRnVO49Q3hKCNWMM8S2uk5ORnh468w9SsaGQpl2HcEXFseCPd130p9jdDWvWQPlhRXL5JlKO5xA01hf/yaP07HWEDdQVxpNkRIjhwGbDdNkixpq3ENuRQ1GBoq3Pl8ZPtvBG5Rji5iczbqr962usDQkmE0ydClOn2ujtHUdFxThKD3qIi6smzH0Mpk076XiXy8WGDRuY8eNLsV6M1QIvNo8HcnL0DGvOHCgrg7IyWhrdFHYnU9A9kajsFcy4PJjojjLUKAd0daGKS3BuK6R+RxmVHeGYJ41jzE8vJTkrYkByrbo6mDsXls1pJKg9EvPof9SXJBiKiZ0YESQZEWK48PGBK64gaOJEpr21jt21ccyZaqJp92acL/6Nba5RmNJSiJ03hpT5sQQGD61vvz4++nqCaWkmIP7E5kWqq2HdOlRtHZoGKncXR+0p5JhuocwxiqmLzNw4C4JoQb39Kof3teE3Khh3aTmlrZEccYwj5toryFocPuCLCycmfvm/sBObEMaSZESI4SYmButD9zKnpQUVHIL/dRDX0kLagTJqt5XS9Kccdv1Gw5yaTMxl48i4frzREXu/gwchJ4fjzVYaO0bhZ3Ozs2wKlZEzyMqCZdPB165g/37c723g0L5u6urgSONYXBOWMHlRKDdNPHUFACFGCklGhDiNo0f1nvbEREhIAIfD6IjOk8kEISH0d7oHBeE7dyrJc6eCx0P7wRqqPinFVd9oZJTDR1oaX3SlsbYSPA4IC9Ov0lw7+WsL6BaX0FVwmG214zluNuOJM9MbFsPyu0IJ96Lxt0IMBElGhDiNuDio31nOB3+w0eEXQVi0lblzYfxw6EQwmXBkxDEuQwqiXQxKwbZt8MknX+2bMeOU4S64UzPY35pBUDLEB+rjRAMDvTDRFWIASDIixBlMuzwUx5ZXqdnTSJd/OL7NUXj8Mo0OSwwxlZX6uNXrrtPHgIaG6msRfZPZDDNHdm01Ic5IkhEhziQoiLSf3U33P7+Ko/MYx3Ka2OtKx3eK0YGJoSQx8esDQi8Ct5u2A5U4K9tJvGbSRbxjIYYuSUaEOAstwMHEX95F3+rXSIyOIGLrhxSQwqb/LWPuHekEBMpUSHEBvqzk9mVhsZ4eKC2lY08xRz45xNE6C/ZZmSReY2yYQgwWr0lGnnnmGdavX09+fj4+Pj40Nzd/622UUjz55JP8/ve/p7m5mblz5/Liiy+Smpo68AGLYcPk8MPn3juhp4eEq66g4OOPid79Hts2bSfqlkVkXpeM2SJJiThHbW2wbh1ceqk+Urq4mM7CckqdoezvTSdo1j8wY8UooqLlPSVGDq9JRnp7e7nxxhuZPXs2L7/88jnd5tlnn+X555/nlVdeISkpiZ/85CdkZ2dTWFiI3W4f4IjFsGK369uJFUvHv/AQUe/toeL1N9nybhQZP8xm1IxYg4P0Mr29dBVXUrfjMM5DjWT85EYcwV7zJ+n8KX1qLxs24GrrxlpaSltQHHkd6exWV5GcHcYV8yAiwuhAhRh8XvPJf+qppwBYvXr1OR2vlOLXv/41//qv/8ry5csBePXVV4mKiuKdd97hlltuGahQxUjg40PMzfOJvHomxat3onp6jY5oaFFK305TVryvrYuDv9tM57Y9tLe49Z1WK4XffwFlsYDZgma16P+3nFhox2LBJzKYCf80b5CfyEXS3g7vvYcqKqaiQl8XpjE8hY3qFiZlmrj7Ega80JkQQ5nXJCPnq7y8nLq6OhYvXty/LygoiKysLHJycs6YjPT09NDT09P/c2trK6CXoXad+FZslC8f3+g4RrJT2sDHTNr9c0/eN9IoBc3NqLp62kvraCqqIy6kg/I5t1N1zE57u35lor1dn02SmWkh6fuXc3TuFLq2ltCVV4TbZCXs1kXg7sPT24fq7UO5+sCt/6tcbiwOH+/9DGganquW8rHP1eQrDTSYlKnx4Nw+gkP0yzHe8pS8tg2GEW9qg3ONUVNKqQGO5aJavXo1q1at+tYxIzt27GDu3LnU1NQQE/PVqpc33XQTmqaxZs2a097u3/7t3/p7Yb7uz3/+M35+ft8pdiGEEGIk6ezs5LbbbqOlpYXALxePPA1De0Yef/xxfv7zn5/1mKKiIjIyMgYpInjiiSf40Y9+1P9za2sr8fHxXHHFFWd9IQeDy+Xio48+4vLLLx+ai4SNANIGJ/N49DGYRUVQUqww1dWQ2pZHmK2dmoxLoaMDS/1R+orK4EgVST7VmNpbaTRHUBs5iYbpV2HytREaYyN8lJ2oeCuRURphYadfONZbX/+KCn0h3/BwffPmsu/e2gbDiTe1wZdXF76NocnII488wl133XXWY5KTky/ovqOjowGor68/qWekvr6ezMzMM97OZrNhs9lO2W+1WodMow+lWEYqaYOvjBmjb0uWQEVFIkePJjJrehea34nKX90JUBBMX54Vrcqiz2aNjASlcHe+TYezm478Xtq2QVu7RnG3DbfFxpT/vpPw9NMPpPC21384TuDztjYYjryhDc41PkOTkYiICCIGaOh4UlIS0dHRbNq0qT/5aG1tJTc3l4ceemhAHlOIkcxkguRkfYOvlSC122HaNCzTpkFTE+zbp08ZGTcOMxAIBHo8xPT0QE8Pns5umup6CE4wtidSCDF4vGYAa1VVFY2NjVRVVeF2u8nPzwcgJSUFx4nFHTIyMvjZz37Gtddei6ZprFq1iv/4j/8gNTW1f2pvbGwsK1asMO6JCDGShYTAggWn7jeZ9Brqvr6YgiFMZkkLMaJ4TTLy05/+lFdeeaX/5ylT9JrcmzdvZuHChQCUlJTQ0tLSf8xjjz1GR0cH999/P83NzVxyySV88MEHUmNECCGEGEK8JhlZvXr1t9YY+ebEIE3TePrpp3n66acHMDIhhBBCfBenGa8uhBBCCDF4JBkRQgghhKEkGRFCCCGEoSQZEUIIIYShJBkRQgghhKEkGRFCCCGEoSQZEUIIIYShJBkRQgghhKEkGRFCCCGEoSQZEUIIIYShJBkRQgghhKEkGRFCCCGEoSQZEUIIIYShJBkRQgghhKEkGRFCCCGEoSQZEUIIIYShLEYHMNQppQBobW01OBJwuVx0dnbS2tqK1Wo1OpwRSdrAWPL6G0/awHje1AZfnju/PJeeiSQj36KtrQ2A+Ph4gyMRQgghvFNbWxtBQUFn/L2mvi1dGeE8Hg81NTUEBASgaZqhsbS2thIfH8+RI0cIDAw0NJaRStrAWPL6G0/awHje1AZKKdra2oiNjcVkOvPIEOkZ+RYmk4m4uDijwzhJYGDgkH8DDnfSBsaS19940gbG85Y2OFuPyJdkAKsQQgghDCXJiBBCCCEMJcmIF7HZbDz55JPYbDajQxmxpA2MJa+/8aQNjDcc20AGsAohhBDCUNIzIoQQQghDSTIihBBCCENJMiKEEEIIQ0kyIoQQQghDSTIyhD3zzDPMmTMHPz8/goODz+k2Sil++tOfEhMTg6+vL4sXL+bQoUMDG+gw1tjYyO23305gYCDBwcHcc889tLe3n/U2CxcuRNO0k7YHH3xwkCL2fi+88AKJiYnY7XaysrLYtWvXWY9/8803ycjIwG63M3HiRDZs2DBIkQ5f59MGq1evPuX9brfbBzHa4eXTTz9l2bJlxMbGomka77zzzrfeZsuWLUydOhWbzUZKSgqrV68e8DgvNklGhrDe3l5uvPFGHnrooXO+zbPPPsvzzz/PSy+9RG5uLv7+/mRnZ9Pd3T2AkQ5ft99+OwUFBXz00Ue89957fPrpp9x///3ferv77ruP2tra/u3ZZ58dhGi935o1a/jRj37Ek08+SV5eHpMnTyY7O5tjx46d9vgdO3Zw6623cs8997B3715WrFjBihUrOHDgwCBHPnycbxuAXgn06+/3ysrKQYx4eOno6GDy5Mm88MIL53R8eXk5S5cuZdGiReTn57Nq1SruvfdeNm7cOMCRXmRKDHl//OMfVVBQ0Lce5/F4VHR0tHruuef69zU3Nyubzab+8pe/DGCEw1NhYaEC1O7du/v3vf/++0rTNFVdXX3G2y1YsED98Ic/HIQIh5+ZM2eq73//+/0/u91uFRsbq372s5+d9vibbrpJLV269KR9WVlZ6oEHHhjQOIez822Dc/37JM4foN5+++2zHvPYY4+p8ePHn7Tv5ptvVtnZ2QMY2cUnPSPDSHl5OXV1dSxevLh/X1BQEFlZWeTk5BgYmXfKyckhODiY6dOn9+9bvHgxJpOJ3Nzcs9729ddfJzw8nAkTJvDEE0/Q2dk50OF6vd7eXvbs2XPS+9dkMrF48eIzvn9zcnJOOh4gOztb3u8X6ELaAKC9vZ2EhATi4+NZvnw5BQUFgxGuYPh8BmShvGGkrq4OgKioqJP2R0VF9f9OnLu6ujoiIyNP2mexWAgNDT3r63nbbbeRkJBAbGws+/bt48c//jElJSW89dZbAx2yV2toaMDtdp/2/VtcXHza29TV1cn7/SK6kDZIT0/nD3/4A5MmTaKlpYVf/OIXzJkzh4KCgiG3yOhwdKbPQGtrK11dXfj6+hoU2fmRnpFB9vjjj58y2Oub25k+9OLiGOg2uP/++8nOzmbixIncfvvtvPrqq7z99tuUlZVdxGchxNAwe/Zs7rzzTjIzM1mwYAFvvfUWERER/O53vzM6NOFFpGdkkD3yyCPcddddZz0mOTn5gu47OjoagPr6emJiYvr319fXk5mZeUH3ORydaxtER0efMmivr6+PxsbG/tf6XGRlZQFQWlrKmDFjzjvekSI8PByz2Ux9ff1J++vr68/4ekdHR5/X8eLsLqQNvslqtTJlyhRKS0sHIkTxDWf6DAQGBnpNrwhIMjLoIiIiiIiIGJD7TkpKIjo6mk2bNvUnH62treTm5p7XjJzh7lzbYPbs2TQ3N7Nnzx6mTZsGwCeffILH4+lPMM5Ffn4+wEkJojiVj48P06ZNY9OmTaxYsQIAj8fDpk2b+MEPfnDa28yePZtNmzaxatWq/n0fffQRs2fPHoSIh58LaYNvcrvd7N+/nyVLlgxgpOJLs2fPPmU6u1d+BoweQSvOrLKyUu3du1c99dRTyuFwqL1796q9e/eqtra2/mPS09PVW2+91f/zf/3Xf6ng4GC1du1atW/fPrV8+XKVlJSkurq6jHgKXu/KK69UU6ZMUbm5uWr79u0qNTVV3Xrrrf2/P3r0qEpPT1e5ublKKaVKS0vV008/rT7//HNVXl6u1q5dq5KTk9X8+fONegpe5a9//auy2Wxq9erVqrCwUN1///0qODhY1dXVKaWUuuOOO9Tjjz/ef/xnn32mLBaL+sUvfqGKiorUk08+qaxWq9q/f79RT8HrnW8bPPXUU2rjxo2qrKxM7dmzR91yyy3KbrergoICo56CV2tra+v/Ww+oX/3qV2rv3r2qsrJSKaXU448/ru64447+4w8fPqz8/PzUo48+qoqKitQLL7ygzGaz+uCDD4x6ChdEkpEhbOXKlQo4Zdu8eXP/MYD64x//2P+zx+NRP/nJT1RUVJSy2WzqsssuUyUlJYMf/DDhdDrVrbfeqhwOhwoMDFR33333SclgeXn5SW1SVVWl5s+fr0JDQ5XNZlMpKSnq0UcfVS0tLQY9A+/zm9/8Ro0ePVr5+PiomTNnqp07d/b/bsGCBWrlypUnHf/GG2+otLQ05ePjo8aPH6/Wr18/yBEPP+fTBqtWreo/NioqSi1ZskTl5eUZEPXwsHnz5tP+3f/yNV+5cqVasGDBKbfJzMxUPj4+Kjk5+aRzgrfQlFLKkC4ZIYQQQghkNo0QQgghDCbJiBBCCCEMJcmIEEIIIQwlyYgQQgghDCXJiBBCCCEMJcmIEEIIIQwlyYgQQgghDCXJiBBCCCEMJcmIEEIIIQwlyYgQQgghDCXJiBBCCCEMJcmIEMIrdXR0cOedd+JwOIiJieGXv/wlCxcuZNWqVUaHJoQ4T5KMCCG80qOPPsrWrVtZu3YtH374IVu2bCEvL8/osIQQF8BidABCCHG+2tvbefnll3nttde47LLLAHjllVeIi4szODIhxIWQnhEhhNcpKyujt7eXrKys/n2hoaGkp6cbGJUQ4kJJMiKEEEIIQ0kyIoTwOmPGjMFqtZKbm9u/r6mpiYMHDxoYlRDiQsmYESGE13E4HNxzzz08+uijhIWFERkZyb/8y79gMsn3KyG8kSQjQgiv9Nxzz9He3s6yZcsICAjgkUceoaWlxeiwhBAXQFNKKaODEEKIi2HhwoVkZmby61//2uhQhBDnQfo0hRBCCGEoSUaEEEIIYSi5TCOEEEIIQ0nPiBBCCCEMJcmIEEIIIQwlyYgQQgghDCXJiBBCCCEMJcmIEEIIIQwlyYgQQgghDCXJiBBCCCEMJcmIEEIIIQz1/wEI3Mguf6W7zAAAAABJRU5ErkJggg==",
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "\n",
        "\"\"\"\n",
        "lets compare with our test_dataset.y values which contains actual labels with H_pred which are predicted values\n",
        "\n",
        "\"\"\"\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "\n",
        "plt.figure(figsize=(6, 6))\n",
        "plt.quiver(\n",
        "    test_dataset.X[:, 0], test_dataset.X[:, 1],  # positions (q, p)\n",
        "    test_dataset.y[:, 0], test_dataset.y[:, 1],  # true derivatives\n",
        "    color='blue', alpha=0.5, label='Ground Truth'\n",
        ")\n",
        "plt.quiver(\n",
        "    test_dataset.X[:, 0], test_dataset.X[:, 1],  # positions (q, p)\n",
        "    H_pred[:, 0], H_pred[:, 1],  # predicted derivatives\n",
        "    color='red', alpha=0.5, label='Predicted'\n",
        ")\n",
        "plt.legend()\n",
        "plt.xlabel(\"q\")\n",
        "plt.ylabel(\"p\")\n",
        "plt.title(\"Vector Field: Ground Truth vs HNN Predictions\")\n",
        "plt.grid()\n",
        "plt.axis('equal')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 564
        },
        "id": "Y6BpQVXEsib8",
        "outputId": "a399d3e8-e8f4-4790-dff2-36810e0a80fb"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "from scipy.integrate import solve_ivp\n",
        "import torch\n",
        "\n",
        "# helper function to call symplectic_gradient\n",
        "def learned_dynamics(t, y):\n",
        "    y_tensor = torch.tensor(y, dtype=torch.float32, requires_grad=True).unsqueeze(0)\n",
        "    dydt = model.symplectic_gradient(y_tensor).squeeze().detach().numpy()\n",
        "    return dydt\n",
        "\n",
        "\n",
        "y0 = test_dataset.X[0] # this is intial state\n",
        "t_span = [0, 3] # simulating from time 0 to 3\n",
        "t_eval = np.linspace(*t_span, 300)\n",
        "\n",
        "# Ground truth trajectory\n",
        "gt_ivp = solve_ivp(dynamics_fn, t_span, y0, t_eval=t_eval)\n",
        "\n",
        "# Learned HNN trajectory\n",
        "learned_ivp = solve_ivp(learned_dynamics, t_span, y0, t_eval=t_eval)\n",
        "\n",
        "# Plot the phase space (q vs p)\n",
        "plt.figure(figsize=(8, 6))\n",
        "plt.plot(gt_ivp.y[0], gt_ivp.y[1], label='Ground Truth', color='blue')\n",
        "plt.plot(learned_ivp.y[0], learned_ivp.y[1], '--', label='HNN Prediction', color='red')\n",
        "plt.xlabel('q (Position)')\n",
        "plt.ylabel('p (Momentum)')\n",
        "plt.title('Phase Space Trajectory: Ground Truth vs HNN Prediction')\n",
        "plt.legend()\n",
        "plt.grid(True)\n",
        "plt.axis('equal')\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GOWNLb7xHhCl"
      },
      "source": [
        "# Congratulations! Time to join the Community!\n",
        "\n",
        "Congratulations on completing this tutorial notebook! If you enjoyed working through the tutorial, and want to continue working with DeepChem, we encourage you to finish the rest of the tutorials in this series. You can also help the DeepChem community in the following ways:\n",
        "\n",
        "## Star DeepChem on [GitHub](https://github.com/deepchem/deepchem)\n",
        "This helps build awareness of the DeepChem project and the tools for open source drug discovery that we're trying to build.\n",
        "\n",
        "## Join the DeepChem Discord\n",
        "The DeepChem [Discord](https://discord.gg/cGzwCdrUqS) hosts a number of scientists, developers, and enthusiasts interested in deep learning for the life sciences. Join the conversation!\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RRcTAQozHhCl"
      },
      "source": [
        "# Bibliography\n",
        "\n",
        "[1] Greydanus, S., Dzamba, M., & Yosinski, J. (2019). *Hamiltonian Neural Networks*. [NeurIPS 2019 Paper](https://arxiv.org/abs/1906.01563)\n",
        "\n",
        "[2] GitHub Repository – [Hamiltonian Neural Networks](https://github.com/greydanus/hamiltonian-nn)\n",
        "\n",
        "[3] Greydanus, S. (2019). *Learning Physics with Neural Networks*. Blog post: [https://greydanus.github.io/2019/05/15/hamiltonian-nns/](https://greydanus.github.io/2019/05/15/hamiltonian-nns/)\n",
        "\n",
        "[4] HNNvsNN Overall Architecture: [https://greydanus.github.io/assets/hamiltonian-nns/overall-idea.png](https://greydanus.github.io/assets/hamiltonian-nns/overall-idea.png)\n",
        "\n",
        "[5] Mass-spring system image: [https://i.ytimg.com/vi/lZPtFDXYQRU/maxresdefault.jpg](https://i.ytimg.com/vi/lZPtFDXYQRU/maxresdefault.jpg)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e92tQCWeHhCl"
      },
      "source": [
        "## Citing This Tutorial\n",
        "If you found this tutorial useful please consider citing it using the provided BibTeX."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Do26XyvDIBtO"
      },
      "outputs": [],
      "source": [
        "@manual{Intro10,\n",
        " title={Mass-spring experiment using HNN},\n",
        " organization={DeepChem},\n",
        " author={Abhay Shinde, José A. Sigüenza },\n",
        " howpublished = {\\url{https://github.com/deepchem/deepchem/tree/master/examples/tutorials/Introduction_to_Hamiltonian_Neural_Network.ipynb}},\n",
        " year={2025},\n",
        "}"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}
